text:
Notes from a New Reading
Notes de relecture
Notas de relectura
Claude Grignon
Translated by Jasmin Smith and Delaina Haslam
Grignon Claude & Passeron Jean-Claude (2015) [1989]. Le Savant et le Populaire. Misérabilisme et populisme en sociologie et en littérature. Paris, Seuil, "Points" [1re éd. Gallimard/Seuil, "Hautes études"]. In Spanish: Grignon Claude & Passeron Jean-Claude (1991). Lo culto y lo popular: miserabilismo y populismo en sociologia y en literatura, Buenos Aires, Ediciones Nueva Vision. Translated from French to Spanish by María Sonderéguer) ; Grignon Claude & Passeron Jean-Claude (1992). Lo culto y lo popular: miserabilismo y populismo en sociologia y en literatura. Translated from French to Spanish by Fernando Alvarez-Uria y Julia Varela. Madrid, Las Ediciones de La Piqueta.2016
Translated from:
Claude Grignon, « Notes from a New Reading », Biens symboliques / Symbolic Goods [Online], 1 | 2017, Online since 15 October 2017, connection on 28 January 2021. URL : https://revue.biens-symboliques.net/128
Inspired by a seminar given at EHESS in 1982, published in different versions and for the first time in the form of a book in 1989 (Grignon & Passeron, 1983, 1985, 2015), Le Savant et le Populaire has not lost any of its relevance. The sociological questions that Jean-Claude Passeron and I wrote about have become "societal questions" that are constantly rehashed in the media; the term "populism" is increasingly popular. The relations between the dominant and the dominated classes, between the "elites" and the People, "real people" or "the man in the street," figure more and more prominently at the centre of opinion debates. The same can be said of that which concerns the "acceptance" of immigrants from foreign cultures: should they assimilate into our culture to be integrated into society, or preserve their cultural identity (i.e., their otherness) at the risk of becoming isolated and excluded?
We are concerned by those topics, but they are not what we are most interested in: we deal with populism in sociology and literature, not in politics. These topics can add obstacles and risks for the sociologist who ventures to study popular and dominated classes and cultures. The political stakes that this study involves run the risk of waking the intellectual "who we know sleeps within every sociologist" (Grignon & Passeron 2015: 117), and of skewing our interpretations, or even our observations, by subjecting them to ideological biases and prejudices. For we sociologists, the relevance of Le Savant et le Populaire is due to the permanence of the sociological questions it addressed, which have never stopped being asked. Regarding eminently social questions, we strove to take the most sociological point of view possible by reviewing and formulating the questions that they pose to sociology. Le Savant et le Populaire is an epistemological exercise, an application of the Bachelardian vigilance to the empirical and mental operations and instruments involved in the sociology of working-class cultures. The theoretical reflections that we pursue, the concepts that we elaborate on, come from a critical inventory of the tools at our disposal; we endeavoured to find out their presuppositions and implicit orientations; what they allow and what they prevent from being seen and known, their limits, their traps, and their drifts.
"Society" and "culture:" these concepts, which are the basis for and at the centre of our analyses, are examples of the kinds of words which are both ordinary and scholarly, which mean "something to everyone" because no one knows exactly what they mean. Let us say that society is what the sociologist studies and culture is what is studied by ethnologists; in this case, it truly is the point of view that creates the object. In Le Savant et le Populaire, we decided to "limit the question to the forms of domination that are at play within a society" (18), in this case contemporary French society. This was a true sociological choice. Sociologies are most often national in scope; the sociologist studies, in the language spoken in the country, the society of which he or she is a member, to which he or she "belongs," on the national, or on a regional or local scale. The sociologist therefore finds himself confronted with the obstacles and limitations the particularities of his object present to generalization and theorization; but this is also the case for ethnologists and historians. The sociologist is the only one, however, to enjoy advantages and suffer from the handicaps that come with proximity: on the one hand, intimate knowledge, familiarity with a culture that he belongs to, most often as a native; on the other hand, risks of ethnocentrism, prejudice tied to social position, and an inability to question the taken-for-granted aspects of the society he studies, and of its culture.
Strictly hierarchical and integrated, as much socially as culturally (compulsory education, the use of French as the common language), this society presented contradictory characteristics that made it and continue to make it particularly interesting. But the social composition of the working classes has changed and the rereading of Le Savant et le Populaire invites us to take these changes into account. The characteristics of the dominated cultures and their relationship with the dominant cultures depend on the properties of the groups that support them. Since the 1980s, the size of the traditional popular classes has diminished; this is especially the case with farmers and, to a lesser extent, workers (who still in 2015 account for more than one fifth of the labour force); this is also true of workers of peasant origin. At the same time, the population of more or less acculturated immigrants, bringing with them many foreign cultures, which are set apart by two essential elements, language and religion, has grown. To what extent can we consider these "faraway cultures," once they have drawn closer and become part of this society, to be "other cultures" in the same way as pre-colonial cultures? Can we apply ethnographic cultural relativism to them without difficulty and without risk? Both autonomous and dominated, these cultures constitute a typical case that the concepts elaborated in Le Savant et le Populaire, such as autonomy and heteronomy, should help to disentangle the ambivalence.
Cultural relativism is as necessary a passage for the ethnologist of popular cultures, who must maintain his distance from his culture of origin to draw nearer to the one he studies, as it is for the sociologist when he attempts to consider these cultures as autonomous. But we run the risk of passing from cultural relativism to a cognitive relativism which, in its extreme form, is based on a radical scepticism for which it is impossible to distinguish what is true from what is false because truth does not exist1. Relativism is fashionable; it applies to intellectual fashion victims, including sociologists through sociologism, which continually tries to go further in the reduction of every element of every culture to arbitrary constructions, all equally deprived of necessity and practical and technical efficiency, that need only be deconstructed to be explained.
Like "culture" and "society," "domination" is one of those common but poorly defined concepts that we are obliged to use because they usually denote the questions and facts that we are concerned with. We strove to pinpoint their meaning not by looking for words that might explain their nature, but by collecting the things and facts—the "mechanisms'—to which they correspond and that they denote2. "Sociology of culture has to first break the monolith represented by the concept of dominated culture" (Grignon & Passeron 2015: 140). This is a task that is unequally difficult to accomplish; the notion of alternation allows us to distinguish between circumstances, fields, interactions, etc., and invites us to find empirical methods with which to do so. Conversely, the notion of ambivalence leaves the door open for interpretation, by suggesting that the most autonomous working class cultures are still, to some degree, dominated—that there is still some of the Same in the Other (and vice versa). "The mischievousness of the interpretative demon" (147) knows no bounds: the most factual descriptions, the most realistic and objective observations are open to interpretation. We interpret them as soon as we analyse them, seek to explain them, comment on them, present them; sociology of culture thereby comes dangerously close to "theories of suspicion," to ideologies and to pseudo-science.
The definition of concepts leads back to the question of the relationship between working-class languages and the language in which the sociologist transcribes them. How can he represent the way subjects speak? To make their speech intelligible, one must translate it; but one cannot translate it without altering it, without causing it to lose its original meaning. George Sand very clearly formulated this aporia (291, note 5). The sociologist thinks and expresses himself spontaneously, naturally, in this dominant form of natural language that is the language of the well-read, the language of his culture, his mother tongue, the language in which he has been trained, that of his professional milieu and of the cultured audience to which his writings are directed. While popular speeches, vernaculars, and "lingoes," are most often oral, sociology is written. The sociologist cannot do without the resources of "literary language which is doubly written" (291), especially its evocative power which helps to elaborate his concepts from observation and which, by tying these concepts to the imagination, allows what they represent to be imagined, and thus allows us to begin to know what they mean; take for example those accounts that are both suggestive and meaningful, which make the reader think by giving him something to see, cf. the works of Richard Hoggart, Marcel Maget, or Marcel Granet (Grignon, 2001). But this evocative power favours interpretative drifts, particularly those which are tied to the free association of words, images and ideas. It is therefore necessary to control it by trying to combine the conflicting principles and demands of literary and scientific writings. While the evocative power of literary language is based on connotation, scientific language depends on denotation. The meaning of a scientific word depends on its deictic capacity; we know what a scientific word means when we know precisely, without ambiguity, what it refers to (Servien, 1935). We will therefore allow ourselves to play with the connotations only for words whose denotation is known. We will be particularly careful regarding the connotations evoked by scholarly terms at every step of the research and for all of those who participate in it, including the interviewer and the interviewees, the sociologist who writes, and the reader whose expectations and reactions he anticipates.
As soon as one makes use of the resources and processes of literary writing, one risks giving in to the influence and attraction of literature. It is difficult for the sociologist who writes not to feel like or want to become an author; just as is the case with the intellectual, an author sleeps within the sociologist. Unless he stops attempting to paint a picture, the sociologist, like the historian, risks foregoing explaining, mixing art with analysis, reality with fiction, sacrificing exactitude to the illusion of truth, as Taine says (1858). When the characteristics that define them have been determined by their evocative power, the types that sociology tries to create approximate literary types and become portraits. Sociology therefore risks taking on literary representations of the worker, the farmer, or the immigrant, as folkloric and populist as they are miserabilist. "The author's narcissism offers an impregnable bastion to class ethnocentrism" (Grignon & Passeron 2015: 313).
Translation and writing difficulties encourage us to pursue the epistemological exercise of Le Savant et le Populaire3. The languages used by the sciences, in which they think and express, are a determinative criterion of their differentiation and their categorization, if not of their hierarchy. Each science, each specialization, can be distinguished by its own words. In this respect, scientific languages have much in common with dialects, professional jargons, regional languages, local patois, etc. As particular, scholarly, and incomprehensible for the layman as they may be, they are variants of natural language. Their translation into ordinary language, for reasons of vulgarisation or instruction, poses the same problems as the translation of a speech or text into a "foreign" language. But the differences between scientific languages cannot be reduced to lexical differences. The principal, fundamental, opposition divides the sciences that think in mathematics and those that think in natural language: on one hand, the sciences of matter, which explain by formulating universal laws that allow prediction; on the other hand, the human sciences, which explain by finding causes, and reconstituting causal sequences that take place in an irreversible time (between the two is biological science, which is split between physics and history—molecular biology versus evolutionary biology or the biology of organisms).
In this regard, sociology belongs to the same family, the same subcategory of science as ethnology and history, that of collective human science. But, at the risk of forgetting that popular cultures are also dominated cultures, the sociologist who wants to be an ethnologist must remain a sociologist. That is why he must combine quantitative and qualitative methods: collecting and processing statistical data in order to establish regularities for lack of laws (the sociologist therefore uses mathematics, but as a tool and not as a language); explaining these regularities by reconstructing (through interviews, observations, case studies, etc.) the processes at the end of which the statistical relationships between the cause (explanatory variables) and effect (explained variables) take place (or not). By reconstructing individual stories, the sociologist gives himself the means of knowing how social determinisms act, but also why they sometimes do not act, and how some exceptional individuals can escape their social destiny. This is the case with Richard Hoggart; the story of his life allows us to know why the mechanisms of reproduction did not work, and, at the same time, to better understand how they function (Hoggart 1988, translated in French: 1991, 2013). But, for the sociologist, exceptional individuals are not unique; by comparing their respective stories, he can group them according to specific traits they share, putting together case clusters, thereby returning to the collective from the individual.
1 For more information about "deniers," cf. Bernard Williams, Vérité et véracité. Essai de généalogie, Paris, Gallimard 2006, cited by Jacques…
2 "Logical-experimental reasonings, which have their base in objective observation, end up using terms only to designate things [...]. Literary…
3 Which I have done in two collective works, themselves products of seminars (Grenier, Grignon, Menger 2001; Grignon & Kordon 2009).
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Weber Max (1958) [1921]. The Rational And Social Foundations Of Music. English Translation by Don Martindale, Johannes Riedel, Gertrude Neuwirth. Carbondale, Southern Illionios University Press.
Wimmer Andreas & Glick Schiller Nina (2002). "Methodological Nationalism and Beyond: Nation–State Building, Migration and the Social Sciences." Global Network, 2: 301-334.
1 For more information about "deniers," cf. Bernard Williams, Vérité et véracité. Essai de généalogie, Paris, Gallimard 2006, cited by Jacques Bouveresse (2008: 281-306).
2 "Logical-experimental reasonings, which have their base in objective observation, end up using terms only to designate things [...]. Literary economists [...] indulge themselves with researching what is value, what is capital, etc. We cannot get them to understand that things are everything and words are nothing. [...] In science, we follow the opposite path; that is to say, we concern ourselves with the thing in question first, then we try to find a name for it" (Pareto, French version, 1917: 48, 53, 55).
Jasmin Smith
Delaina Haslam


text:
We made you a Spotify playlist for your next karaoke party
You need more karaoke in your life.
By Nicole Gallucci on September 15, 2018
Belt it out, people. Credit: mashable composite: bob al-greene/mashable and shutterstock
This is You Won't Regret It, a new weekly column featuring recommendations, tips, and unsolicited advice from the Mashable culture team.
When was the last time you stepped up to a microphone, abandoned all fear of embarrassment, and passionately belted the lyrics to one of your favorite throwback jams?
If your answer falls within the past two weeks, I'd like to congratulate you on knowing how to live. But if it's been a while since you've read lyrics from a monitor and bared your soul into a mic, I'm here to inform you that you're in desperate need of a karaoke night.
SEE ALSO: HitClips: Remembering the most absurd way we listened to music
Anyone who's ever performed a mini concert in the comfort of their shower or pretended to be a guest on Carpool Karaoke knows that singing out loud, without restraint, feels amazing. Now imagine that satisfying sensation, intensified — with some good food, drinks, lighting, and friends surrounding you — and you've got a karaoke night. Sounds great, right? That's because it is!
Most people know that listening to music does wonders(Opens in a new window) for your psyche, but the act of singing has some benefits, too. A 2017 study(Opens in a new window) that examined 1,779 choir members internationally for four months found "confirmatory evidence to support choral singing as a means of improving wellbeing." And earlier this year, the Chicago Tribune reported(Opens in a new window) that singing can lower cortisol levels (i.e.: stress hormones,) help improve mental functions, and more.
Beyond potential health benefits, those who haven't spent a night at a karaoke bar are missing out on a magically cathartic experience. Sing-screaming the scathing lyrics to your favorite emo songs or belting the words to a classic hit you'll never do justice to is one of more underrated forms of stress relief. It's an innocent way to release bottled up emotions that's both fun and humbling.
And we'd be remiss not to mention that a karaoke adventure provides an opportunity to post what I believe is one of the best types of Instagram photos out there: The Karaoke Lyrics Sub-Gram. Posting karaoke lyrics to Instagram is kind of like a sub-tweet, but you let the screen do all the talking. It's pretty much the closest thing we have to AIM away message song lyrics. Truly powerful stuff.
Avril knows best. Credit:
Karaoke often comes easily to confident singers, but for the many introverts of the world like myself, the thought of publicly singing into a microphone in front of strangers can feel terrifying.
While it might seem intimidating at first, as someone who's sat out her fair share of karaoke opportunities before making it to the mic, I promise you it's worth trying.
But if you'd rather gently ease yourself into the karaoke life, you can start by practicing alone in the comfort of your own home, like Cameron Diaz in The Holiday, or hosting a karaoke party to sing in front of people you already know.
If you don't have a karaoke machine, there are tons of options on Amazon like BONAOK's Wireless Bluetooth mic(Opens in a new window), a fun and flashy Singing Machine(Opens in a new window), or the Singtrix Party Bundle(Opens in a new window) home karaoke system that includes a mic stand, "live vocal effects technology," and a speaker if you want to go all out.
You can also search the app store for singing apps(Opens in a new window), or improvise by searching instrumental karaoke versions of songs on YouTube. And if you do decide to go to a karaoke bar, don't forget that you always have the option to opt for a classic duet or group number if you'd like some company at the mic.
You can can never go wrong with any song by ABBA(Opens in a new window), or anything that's been featured on Lip Sync Battle(Opens in a new window) or Glee(Opens in a new window). And Lorelai from Gilmore Girls showed us(Opens in a new window) that Whitney Houston's "I Will Always Love You(Opens in a new window)" is the perfect song for karaoke-related grand romantic gestures.
Still unsure where to start? That's fine. We made you this playlist of suggestions. Good luck up there.
Want more culture writing beamed directly to your inbox? Sign up here for the twice-weekly Click Click Click newsletter. It's fun – we promise.
Serenade the world with this portable karaoke microphone
Nicole Gallucci
Nicole is a Senior Editor at Mashable. She primarily covers entertainment and digital culture trends, and in her free time she can be found watching TV, sending voice notes, or going viral on Twitter for admiring knitwear. You can follow her on Twitter @nicolemichele5(Opens in a new window).
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redpajama_set_name: RedPajamaCommonCrawl


For anyone wondering, I ran a google image search for the word "actress". I counted 53 before I found a man. I also searched "actor"; I counted 1 before I saw a woman.
Actor is technically a unisex term so it makes sense you would see both.
Regular Civ VI players in Britain or Europe?
Just wondering if there's anyone that regularly plays Civ or has a group that regularly plays that I could be a part of, I say Britain or Europe so there aren't major rime difference worries.
FYI, the links don't work anymore, could we get another?
https://chat.whatsapp.com/CXzJijzvBNnClOW4HjQaNt This is a WhatsApp group I am in for civ6 multiplayer.
Is it bad to always be restarting games?
Can I make a National Park here?
What kind of map are you playing on?
Hey, I'm no god tier player but I've got 160 so hours so I'd say I'm good at the game. I've been looking for someone to play with as well so I'd be happy to help.
Yeah I've got a friend who doesn't play that much but he would occasionally.


Located in the beautiful State of Baja California Sur, facing the Gulf of California and sheltered by the majestic Sierra de La Giganta, is a wonderful place with a warm climate and bountiful natural riches. It may seem like Mother Nature created a model of perfect landscapes, flora and fauna for the delight of those who live here. As a result, we are committed to preserving them in order for each one of our visitors to enjoy.
Loreto had its beginnings in the primitive ages. The first human settlers were tribes called Cochimies, Pericues and Guaycuras. They left their mark on the land with several petroglyphs in different corners of La Giganta. The paintings on the cliffs are similar and contain profiles of human faces. They are one of the reasons we have such a deep love and respect for this land.
The sea represents the year 1697. That is when Father Juan María de Salvatierra stepped off a boat onto our beach and began the Jesuit Evangelization and the founding of the Camino Real Misionero. The series of more than 40 missions extended to what today is Sonoma, California. The arrival of Father Juan marked the beginning of colonization of the entire peninsula and built the foundation for the towns and cities of today.
There's much more to Loreto than history. The nearby sea is a National Marine Park formed by five islands and declared by UNESCO as a World Heritage Site in 1997 for the endemic flora and fauna. The famous French diver, Jacques Cousteau, called the waters off Loreto the natural entrance to the largest aquarium in the world. Due to their unparalleled characteristics, the waters off Loreto contain the only Blue Whale Sanctuary, the largest mammal on the planet, as well as more than 260 of 400 marine species that inhabit the Gulf of California.
Loreto maintains that small-town feel, safe and quiet. Just a walk through the historic center or some land or aquatic activity is a special experience and one that all members of a family will remember for life. No wonder visitors want to return as soon as possible. If that weren't enough, the food is a unique experience. The Chocolata Clam is a dish that has been enjoyed from cavemen on the peninsula to locals and visitors today. The traditional food is prepared with the same millenary recipe, the famous Tatema of Clam.
We are very happy that you can read these articles. When you travel in the near future, you'll want to live the Magic of Loreto.


The timetable has been kept at the narrow day width so that 18 months can fit onto a single screen. This example shows how Venus changes from being a prominent evening object in early 2004 to a morning object in late 2004.
The moon display has been turned off here because it doesn't affect the visibility of something as bright as Venus.


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text:
How to Choose an SSD
by Lettie
Fast, performance-enhancing and durable. SSDs are taking over the once hard drive market, but which ones are worth buying?
Lately, the challenge between hard drives and SSDs seems to have been won by the latter. Solid state drives offer faster transfer rates, consume less power and are also more durable. If we don't have a lot of knowledge on the subject though, it's not easy to buy an SSD.
To understand how to get around in the world of SSDs, let's see what features we absolutely need to take into consideration before buying a solid state drive. Let's start by saying that after a great success on laptops now SSDs are finding more and more way on desktops as well. Let's start with the interface. The most recommended is Serial ATA. It is the latest generation interface for these devices and therefore offers the best performance. To make sure you get one of the best possible purchases the most recommended choice at the moment could be a 6GB SATA.
Data on SATA interfaces
It's good to remember that interfaces indicate the data writing speed. A 6GB SATA III guarantees a speed of 750MB per second. A little worse is the 3GB SATA II which stops at 375MB per second. The first generation SATA has a writing speed of 187.5MB per second. It must be said, however, that these data are recorded under optimal conditions that will almost never be replicated on your machines. So always try to understand your needs before buying. To be more exhaustive we can say that on a computer generally SATA III have a speed of 500-600MB per second. There are also new interfaces that are entering the market recently. For desktops a new solution is the SATA Express. This solution increases storage performance to 2GB per second. Yet these are not even the fastest models.
M.2 Interface
M.2 is a fairly new interface for SSDs. It is not a different technology from SATA but the drive being structured differently is much better performing than older SATA solutions. This is a solution that lately is used a lot on notebooks, especially in the ultra-thin ones. Compared to a SATA interface the main difference is the shape. Performance ranges from 4GB to 8GB per second.
Physical limits
If we are thinking of installing a solid state drive on our laptop we have to consider the compatibility of the SSD size with our notebook. Generally, the dedicated space on laptops is 2.5 inches with a height ranging from 5 millimeters up to 9.5 millimeters, depending on the machine. Fortunately most M.2 and SATA are compatible with these measurements. However, it is not advisable to buy blindly and without inquiring about compatibility. For example, some latest generation and ultra-thin notebooks can only support M.2.
This is a basic feature, and it is not hard to see why. These solutions are designed to save as much data as possible based on our needs. In the beginning, SSDs with a lot of storage space were quite expensive, but prices have come down considerably in the last period. Average values of solid state drives range from 64Gb to 4TB.
Write cycles
SSDs have a life marked from birth. Each solid state drive has a finite number of cycles it can complete before it no longer works. This is a very important aspect to consider before purchasing. The average life of a SSD according to the reports of the manufacturers ranges from 3 thousand to 5 thousand writing cycles. Attention then to the cleaning system present by default on many SSD solutions that allows you to eliminate junk files and amplify performance but at the same time also shortens the life of the solid state drive. To avoid this inconvenience, it is best to choose an SSD with TRIM function. A program that optimizes the cleaning and does not make it detrimental to write cycles.
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text:
Hart Family History
Ruby[1, 2, 3]
Name Ruby
Born 30 Aug 1916 New York [2, 3]
Residence 1 Apr 1940 Rochester, Monroe, New York, United States [2]
Residence 1943 Rochester, New York, USA [1]
_UID F9D621BDC6684A0F97717287A12624486850
Died Nov 1986 Ontario, Wayne, New York, United States of America [3]
Person ID I1572 Our Genealogy
Last Modified 24 Mar 2016
Family Donald F Surline, b. 19 Apr 1915, Canada , d. 18 Feb 1986, Ontario, Wayne, New York, United States of America (Age 70 years)
1. Ronald Surline, b. 9 Mar 1938, New York , d. 12 Mar 2012 (Age 74 years)
[S224] U.S. City Directories (Beta).
Residence date: 1943
Residence place: Rochester, New York, USA
[S230] 1940 United States Federal Census.
Birth date: abt 1917
Birth place: New York
Residence date: 1 Apr 1940
Residence place: Rochester, Monroe, New York, United States
[S311] Social Security Death Index, Number: 128-09-6222; Issue State: New York; Issue Date: Before 1951.
Helpful Genealogy Links
1889-1965 Mix
Old Album
Hart & McLean Family Albums
Copyright © 2008 - 2021 Hart Family History - All Rights Reserved.


text:
british journal of cancer
Comprehensive small RNA-sequencing of primary myeloma cells identifies miR-105-5p as a predictor of patient survival
Expanding the repertoire of miRNAs and miRNA-offset RNAs expressed in multiple myeloma by small RNA deep sequencing
Luca Agnelli, Andrea Bisognin, … Antonino Neri
miRNA-seq and clinical evaluation in multiple myeloma: miR-181a overexpression predicts short-term disease progression and poor post-treatment outcome
Maria-Alexandra Papadimitriou, Aristea-Maria Papanota, … Andreas Scorilas
RNA-Seq profiling of deregulated miRs in CLL and their impact on clinical outcome
Gurvinder Kaur, Vivek Ruhela, … Ritu Gupta
Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma
Mehmet Kemal Samur, Stephane Minvielle, … Nikhil C. Munshi
Genome-wide identification of potential biomarkers in multiple myeloma using meta-analysis of mRNA and miRNA expression data
Amit Katiyar, Gurvinder Kaur, … Ritu Gupta
A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma
Domenica Ronchetti, Luca Agnelli, … Antonino Neri
MicroRNA21 and the various types of myeloid leukemia
Mani Panagal, Senthil Kumar S. R., … Durairaj Sekar
Identification of miR-320 family members as potential diagnostic and prognostic biomarkers in myelodysplastic syndromes
Chengyao Wan, Jing Wen, … Zhenfang Liu
Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells
Sarah M. Hücker, Tobias Fehlmann, … Stefan Kirsch
Kristin Roseth Aass1,2,
Tonje Marie Vikene Nedal1,2,
Siri Anshushaug Bouma2,
Synne Stokke Tryggestad1,2,
Einar Haukås3,
Tobias Schmidt Slørdahl ORCID: orcid.org/0000-0001-7488-48632,4,
Anders Waage ORCID: orcid.org/0000-0001-9072-12202,4,
Therese Standal ORCID: orcid.org/0000-0003-3314-85221,2,4 na1 &
Robin Mjelle ORCID: orcid.org/0000-0003-3509-41342,5,6 na1
British Journal of Cancer (2022)Cite this article
Non-coding RNAs
Prognostic markers
Small RNAs (sRNAs), a heterogenous group of non-coding RNAs, are emerging as promising molecules for cancer patient risk stratification and as players in tumour pathogenesis. Here, we have studied microRNAs (miRNAs) and other sRNAs in relation to survival and disease severity in multiple myeloma.
We comprehensively characterised sRNA expression in multiple myeloma patients by performing sRNA-sequencing on myeloma cells isolated from bone marrow aspirates of 86 myeloma patients. The sRNA expression profiles were correlated with the patients' clinical data to investigate associations with survival and disease subgroups, by using cox proportional hazards (coxph) -models and limma-voom, respectively. A publicly available sRNA dataset was used as external validation (n = 151).
We show that multiple miRNAs are differentially expressed between ISS Stage I and III. Interestingly, we observed the downregulation of seven different U2 spliceosomal RNAs, a type of small nuclear RNAs in severe disease stages. Further, by a discovery-based approach, we identified miRNA miR-105-5p as a predictor of poor overall survival (OS) in multiple myeloma. Multivariate analysis showed that miR-105-5p predict OS independently of established disease markers.
Overexpression of miR-105-5p in myeloma cells correlates with reduced OS, potentially improving prognostic risk stratification in multiple myeloma.
Multiple myeloma is incurable cancer arising from the clonal proliferation of terminally differentiated plasma cells in the bone marrow. Myeloma accounts for about 10% of all haematological malignancies [1]. Clinical manifestations include high levels of monoclonal antibodies in serum and urine, anaemia, multiple organ failure, immune suppression and bone disease [1]. Major improvement of treatment has increased median OS from 2.5 year in 1997 to more than 6 years as of today [2]. Today, about 16% of patients are long-term survivors with OS of more than 8 years [3], but still, nearly a quarter of patients continue to have median OS of only 2–3 years [4]. The International Staging System (ISS) has since 2005 been the standard risk stratification system for myeloma and is based on two parameters; level of serum β2-microglobulin which reflects tumour mass and renal function, and level of serum albumin which reflects bone marrow inflammation [5]. This score identifies three patient Groups, I, II and III, with different prognoses [1]. In 2015, the Revised-ISS (R-ISS), including also high-risk chromosomal abnormalities and serum lactate dehydrogenase levels, was introduced [6]. However, myeloma is a heterogenous disease with OS ranging from 3 months to more than 20 years. In light of the great inter-patient variability, there is need for further differentiation of patients for the use of more personalised, risk-adapted treatment approaches [7].
sRNAs are defined as non-coding RNA molecules shorter than 300 nucleotides in length [8]. miRNAs are among the most studied groups of sRNAs, and play an important role in gene regulation in human tissues [9]. miRNA biogenesis starts with transcription of a larger primary transcript in the nucleus. Following the processing by nucleases, a stem-loop-structured precursor miRNA is transported into the cytosol. The ~22 nucleotide long miRNA duplex is loaded onto a RNA-induced silencing complex (RISC) while one of the strands is degraded. The RISC complex mediates the degradation of mRNA targets through a 3´UTR complementary target site to the miRNA [9]. miRNAs repress gene expression by either mRNA cleavage or translational repression, depending on the degree of target complementarity [9]. miRNAs are frequently dysregulated in cancers due to defects in the miRNA biogenesis machinery, abnormal transcriptional regulation, epigenetic changes and amplification or deletion of miRNA genes, and may act both as tumour suppressors and oncogenes [10]. miRNAs have become increasingly popular as biomarkers for disease, mainly due to their stability in tissue and circulation and their frequent dysregulation in disease. miRNAs are easily isolated from circulation and are also more stable in formalin-fixed, paraffin-embedded (FFPE) material and other biopsy specimens than messenger RNAs (mRNAs), and may therefore be particularly suitable as biomarkers [11].
Many miRNAs are differentially expressed in myeloma patients compared to healthy controls, and miRNAs may promote tumour progression by influencing the survival and proliferation of myeloma cells [11]. In addition, miRNA expression has been linked to distinct molecular subgroups and prognosis [11]. Several studies have identified circulating miRNAs in serum and plasma as predictors of progression-free survival (PFS) and OS in myeloma [12, 13], but the cellular sources of circulating miRNAs are largely unknown. Among endogenously expressed miRNAs from primary myeloma cells, miR-15a, miR-33b, miR-17, miR-886-5p and miR-181a have been identified as prognostic factors by qPCR- and microarray-based methods [14,15,16]. These survival-associated miRNAs were identified after being detected as differentially expressed in multiple myeloma or between ISS subgroups and significance was not adjusted for multiple testing across all expressed miRNAs in the cell.
While miRNAs represent a highly studied class of sRNA in myeloma, other types of sRNA have been largely overlooked. In recent years, the sRNA landscape has expanded and the expression of sRNAs is shown to be more widespread than previously anticipated. sRNA-seq can detect several types of sRNAs, such as transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), small nuclear RNAs (snRNAs), long non-coding RNAs (lncRNAs) and piwi-interacting RNAs [17]. In cancer research, there has been an undeserved lack of attention to sRNAs, which are essential in "house-keeping" processes in the cells, including RNA splicing (snRNAs) and amino-acid peptide elongation (tRNAs) and posttranslational modifications (snoRNAs) [9, 18,19,20]. These essential cellular processes are often dysregulated in cancer and may reflect the influence of sRNAs on tumorigenesis. An obstacle in evaluating sRNA dysregulation and differential expression in diseased vs non-diseased tissue has been the quantification of sRNA levels, due to the lack of poly(A) tails and the presence of other molecular modifications, however, current sRNA-seq technologies have proven efficient in mapping most classes of sRNAs [8, 21]. More recently, many classes of sRNAs are shown to have prognostic value and to play functional roles in cancer [8]. For example, dysregulation of snRNAs, which are important components of the spliceosome, may affect the splicing of tumour-suppressor or oncogenic transcripts [22] and have prognostic value [8].
Here, we performed comprehensive sRNA-seq on CD138 + cells isolated from bone marrow aspirates of 86 myeloma patients. We characterised differential sRNA expression between disease stages and analysed if expression of sRNAs was associated with survival. The data are available in an interactive web application that can be used to explore the relation between sRNAs and clinical parameters, including patient survival. In the current study, we found novel associations between snRNAs, miRNAs and ISS stage. Further, by a discovery-based approach, we identified miR-105-5p expression in myeloma cells as a prognostic factor for patient OS.
Patient cohort
The patient cohort consisted of 86 multiple myeloma patients with a median age of 67 (31–88) years, all diagnosed with myeloma C90.0. The patient's bone marrow samples were obtained at the time of diagnosis. The patients were diagnosed in the 2012–2017-year interval in Norway, and samples were stored in Biobank1, the research biobank of the Central Norway Regional Health Authority. Patients were stratified based on the original ISS system and 34.8%, 20.9%, 32.5% of the patients were classified in Stages I, II and III, respectively, while for 11.6% of patients' ISS stage was not determined. The cytogenetic abnormalities del(17p13) and t(4;14), were evaluated by fluorescence in situ hybridisation (FISH) analysis, while bone disease were determined either by X-ray when diagnosed before 2014 (N = 24), or whole-body low-dose computed tomography (CT) when diagnosed after 2014 (N = 62). The median PFS and OS for the patient cohort were 27 and 57 months, respectively. Further details about the patients' clinicopathological characteristics are summarised in Table 1.
Table 1 Clinical and histopathological characteristics of the investigated patient cohort.
The Regional Committee for Medical and Health Research Ethics (REK2011/2029) approved the study, and all patients provided written informed consent.
Isolation of CD138 + plasma cells and patient selection
CD138 + plasma cells were isolated from bone marrow aspirates obtained at diagnosis. The cells were isolated by RoboSep automated cell separator using Human CD138 Positive Selection Kit (StemCell Technologies, Grenoble, France) [23]. The purity of plasma cell isolates as estimated by counting plasma cells on cytospins was >95%. The cells were pelleted and stored at −80 °C at the hospital biobank (Biobank1, St. Olavs University Hospital HR, Trondheim, Norway). Before the sequencing experiment, 86 samples were randomly selected from the biobank without prior knowledge of the groups and investigations performed in the current study. The sample size was chosen based on available samples in the biobank, experience from similar studies by the authors, and sample sizes form similar published studies in multiple myeloma.
RNA isolation, library preparation and sequencing
RNA for sRNA-seq was isolated using miRVana total RNA isolation, following the protocol, (ThermoFisher, #AM1560). sRNA-seq libraries were randomly prepared from 400 ng of RNA using the NEXTFLEX Small RNA-Seq Kit v3 (PerkinElmer, #NOVA-5132-05) using 16 PCR cycles and using the thermal settings as recommended in the protocol. Ten synthetic calibrator RNAs were mixed with the input RNA during the first ligation step as previously described [24]. After library preparation, sRNAs quality and size were evaluated using Eukaryote 4 total RNA pico assay on the 2100 Bioanalyzer (Agilent Technologies) and sRNA-fragments with size larger than 140 nts (adaptors are 140 nts) and shorter than 413 nts (longest detected fragment) were excised and included in the sequencing.
Bioanalyzer result is presented in Supplementary Fig. 1C. The sequencing libraries were sequenced on the NextSeq 500 System from Illumina.
mRNA-seq was performed on the same patient samples and these data can be accessed in the web application together with the sRNA data. The methods and workflow for the sequencing and analysis of mRNA data are published and previously described [25].
Data processing of sRNA-seq
The raw sequencing data were processed using the following procedure: quality control of the raw sequence data was performed using fastQC [26] trimming of sequence adaptors and random nucleotides from the 3'- and 5' end of the raw sequences was performed using cutadapt-1.2.1 [27]. The trimmed sequences were collapsed with the fastx collapser tool [28] into single unique reads along with their total read count and mapped to the human (hg38) genome using bowtie2 [29] allowing for up to ten alignments per read to account for reads from duplicated miRNA loci (bowtie2 – k10), and else default parameters. MiRNA-counts were calculated using htseq-count from the HTseq python package [30]. These reads were further filtered to identify those with perfect alignment to the genome, and the total read count for mature miRNAs were then computed by summing the total read count per sequence (isomiR) overlapping each miRNA locus. Mature miRNAs and non-coding RNAs were annotated using miRBase (Release 22, 2014) and RNA Central release 17 (http://rnacentral.org), respectively. In order to compare miRNA expression between samples, read counts were normalised using the calibrator RNA normalisation factors calculated in limma, followed by counts per million (cpm) normalisation. The calibrator RNAs were not filtered prior to normalisation and the calcNormFactors in limma were calculated using the full calibrator count matrix.
Differential expression analysis
Differentially expressed sRNAs were detected using the limma (v3.5) package in R with voom transformation [31]. Limma-voom robustly estimates the mean-variance relationship in the data and work with log-cpm normalised counts which enables statistically robust differential expression analysis. The statistical tests in limma-voom are applied after performing mean-variance normalisation, ensuring that standard statistical test such as t test can be applied to counts data. The count matrices were filtered to contain RNAs that were expressed with at least 1 cpm in at least 25% of the samples. The analyses were adjusted for the patient's age and sex. P value adjustment was performed using Benjamini–Hochberg. The R-script used to detect differentially expressed sRNAs can be found in the Supplemental Information.
Survival analyses
Survival analyses are performed using a coxph model in R using the survival package and the functions coxph and Surv. Each sRNA-class was analysed individually, and the P values were corrected for multiple testing across all sRNAs within each sRNA-class using the function qvalue in R. The discovery survival analysis was adjusted for age, sex and ISS. The R-script for survival analyses is available in Supplemental Information.
Multivariate analysis on miR-105-5p specifically was performed using coxph by including clinical parameters that were significantly associated with OS as covariates in the model, including age, sex, ISS, haemoglobin, creatine, calcium, albumin and B2M. The R-script for the multivariate analysis can be found in Supplemental Information.
Kaplan–Meier survival curves and calculation of cutoff value
The Cutoff algorithm was applied to determine the optimal cutoff point for high- and low expression of the miRNAs. Specifically, the normalised expression matrix was uploaded to Cutoff Finder (https://molpathoheidelberg.shinyapps.io/CutoffFinder_v1/) and the cutoff values were determined using the "Fit of mixture model" method. These cutoff values were applied to both the discovery and validation dataset. For miR-105-5p, the cutoff values were High: log2cpm > 1.031 and Low: log2cpm ≤ 1.031. The survival curves were plotted and calculated using the function ggsurvplot within the R package survminer. The script can be found in Supplemental Information.
Analysis of validation cohort
Kryukov et al. [32] performed microarray RNA profiling by using the Affymetrix GeneChip Human Gene 1.0 ST Array in CD138 + plasma cells from 151 newly diagnosed untreated multiple myeloma patients. The survival data and processed expression data from this study were downloaded from EMBL-EBI ArrayExpress (accession number: E-MTAB-1038 and E-MTAB-4032). This microarray array also contains probes for several human miRNAs. The miRNA probes were identifies using biomaRt in R using the annotations available at Affymetrix: http://www.affymetrix.com/support/technical/byproduct.affx?product=hugene-1_0-st-v1. The expression data for miR-105-5p were extracted and plotted using ggsurvplot in R as described.
sRNA-sequencing of CD138 + cells from multiple myeloma patients
To identify sRNA associated with disease severity and OS in multiple myeloma, we performed sRNA-seq on RNA isolated from purified bone marrow plasma cells from 86 patients at diagnosis (Table 1 and Supplementary Table S1). The main steps of the study workflow are presented in Fig. 1. On average, 54 million reads mapped to the human genome (Supplementary Fig. 1A). We detected a total of 1757 unique miRNAs and 161 of those were expressed with at least 1 count per million (cpm) in all 86 samples. The highest expressed miRNA was miR-148a-3p, and six miRNAs contributed with about 50% of the reads in the libraries (Fig. 2a).
Fig. 1: Workflow of the sRNA-seq study.
Small RNAs isolated from bone marrow aspirates from 86 multiple myeloma patients were sequenced using high-throughput sequencing. MiRNAs and other small RNAs were identified and quantified by using the databases miRBase and RNACentral, respectively. The expression data was analysed with respect to the patient's clinical data. An independent cohort with miRNA expression data was used to validate the results from the survival analysis.
Fig. 2: sRNA expression and its correlation with disease stage.
a Cumulative expression of the top 20 highest expressed miRNAs. b Differentially expressed miRNAs between ISS Stage III and I. Bonferroni-adjusted-P values determined by limma in R. The number of patients within each group is shown in the legend. Note that for some patients, ISS information is lacking. c Relative abundance of the main sRNA classes identified, summed across all samples. d Differentially expressed snRNAs between ISS Stage III and I. The IDs show the RNA-type and gene-ID. See (b) for the explanation of the legend. The following snRNAs were located within a host gene: URS0000690F87 in gene RUVBL1; URS00006BFA75 in gene GSKIP; URS00006DE490 in gene ITF88; URS0000A90D33 in gene CCDC200.
miRNAs differentially expressed between myeloma disease stages
We investigated if any of the expressed miRNAs were differentially expressed between patients with ISS Stage III (high-risk disease) and patients with ISS Stage I (low-risk disease). We detected seven significantly differentially expressed miRNAs, let-7c-5p, miR-125-2-3p, miR-125-5p, miR-3648, miR-3916, and miR-99a-5p, which were upregulated in Stage III compared to Stage I. One miRNA, miR-873-5p, was expressed lower in ISS Stage III compared with Stage I (Fig. 2b). For the significant miRNAs, we observed a linear trend in expression from Stage I to II to III, supporting that the expression is associated with disease severity. When adjusting for ISS stage, none of these sRNAs were associated with OS (Supplementary Table S2).
U2 spliceosomal snRNAs are differentially expressed between myeloma disease stages
In addition to miRNAs, we detected sRNAs from several other sRNA classes. The most abundant class of sRNAs were lncRNAs, rRNAs, snoRNAs and tRNAs (Fig. 2c and Supplementary Fig. 1A, B). The distribution of sRNAs in the samples was equivalent to that observed in solid tumour cancers [33]. Motivated by the significant associations between miRNAs and ISS stage, we investigated if any of the other classes of sRNAs were differentially expressed in ISS stage. We detected significant changes in seven snRNAs, all of which showed decreased expression in Stage III compared to Stage I (Fig. 2d). All seven ISS-associated snRNAs belonged to the U2 spliceosomal RNA class, although transcribed from different genomic loci. To investigate if the changes in snRNA expression were related to changes in the transcription of the corresponding loci, we identified potential host genes of these snRNAs and investigated if the host genes were related to ISS stage. Four of the seven snRNAs were located within a host gene (see figure text in Fig. 2d), however, we did not observe any significant associations between the host gene expression and ISS stage (data for host gene expression not shown), indicating that the changes in snRNA expression are not directly linked to changes in the transcription of the corresponding loci, but rather a sum of different regulatory factors.
miR-105-5p is associated with reduced OS in multiple myeloma
Having shown that multiple miRNAs and other sRNAs are associated with the myeloma disease stage, we investigated if miRNAs or other sRNAs can predict OS and PFS. Using cox proportional hazards regression (coxph) with adjustment for multiple testing across all expressed miRNAs and likewise for the other sRNAs, we detected one miRNA, miR-105-5p, to be significantly associated with OS. No other miRNA or sRNA were significantly associated with PFS or OS after adjustment for multiple testing. High expression of miR-105-5p was associated with shorter OS (HR: 2.9; 95% CI: 1.57–5.3; P value: 0.00067 and 0.02 before and after correcting for multiple testing, respectively). The optimal cutoff point for high and low miR-105-5p was calculated using Cutoff Finder [34], which split the data at the 57th percentile, resulting in 36 patients in the high-group (log2cpm > 1.031) and 50 patients (log2cpm ≤1.031) in the low-group (Supplementary Fig. 2A). The Kaplan–Meier survival curves for miR-105-5p showed clear differences in median survival between the groups (3313 days for the "miR-105-5p low" group and 1398 days for the "miR-105-5p high" group) (Fig. 3a). MiR-105-5p was also associated with PFS (HR: 1.84; 95% CI: 1.1–3.1; P value: 0.02) (Fig. 3b). Next, we performed OS univariate coxph for the available clinical parameters for the patient cohort. We identified seven clinical parameters to be significantly associated with OS of which age, ISS stage, creatine, calcium and beta-2 microglobulin (B2M) were negatively associated with OS (HR > 1) and Haemoglobin and Albumin were positively associated with OS (HR < 1) (Fig. 3c). We did not find any significant association with the two available high-risk cytogenetic aberrations, deletion 17p13 and translocation (4;14), most likely due to small N (Supplementary Fig. 2B, C). We then evaluated the independent prognostic value of miR-105-5p with respect to OS by adjusting for age, sex, ISS stage, haemoglobin, creatine, calcium, albumin and B2M in a coxph model. The multivariate OS model showed that miR-105-5p retained its prognostic value (HR: 3.6; 95% CI: 1.56–8.5; P value: 0.002) (Fig. 3d). Combining miR-105-5p expression and ISS groups in a coxph-analysis showed that patients with high miR-105-5p and high ISS (ISS III) had significantly poorer survival compared to patients with low miR-105-5p and high ISS (HR: 4.98; 95% CI: 1.65–15; P value: 0.004) (Supplementary Fig. 3A and Supplementary Table S3). The patients with ISS III and high miR-105-5p had median OS of 804 days, while the patients with ISS III and low miR-105-5p lived 2480 days, indicating that miR-105-5p distinguish the high-risk patients. The multivariate PFS survival model was, however, not significant (HR: 1.85; CI: 0.9–3.8; P value: 0.09), although pointed in the same direction as the univariate PFS survival model.
Fig. 3: miR-105-5p associates with reduced OS.
a Kaplan–Meier OS curves for miR-105-5p in the discovery cohort. The "+" sign on the curves indicates censored patients. The number of patients at risk at each interval is shown. At diagnosis, 36 patients had a high miR-105-5p expression, and 50 patients had low miR-105-5p expression. The P value is calculated by the log-rank test in the coxph-function in R. Hazard ratio and confidence interval are calculated by the coxph-function in R. b Kaplan–Meier PFS survival curves for miR-105-5p in the discovery cohort. At diagnosis, 35 patients had high miR-105-5p expression, and 47 patients had low miR-105-5p expression. Statistics calculated as described in a). c Forest plots for the univariate cox regression analyses of clinical parameters with respect to OS. Shown are parameters that were detected as significant, in addition to age which was not detected as significant. Statistics calculated as described in a). d Multivariate cox regression analysis of miR-105-5p with respect to OS adjusted for age, sex, ISS stage, haemoglobin, creatine, calcium, albumin and beta-2 microglobulin (B2M). Statistics calculated as described in a). e Kaplan–Meier OS curve for miR-105-5p in the validation cohort of the Kruykov et al. [32] Statistics calculated as described in a).
To validate the prognostic value of miR-105-5p, we analysed the microarray dataset of Kryukov et al. (n = 149) [32]. Supporting the results from the discovery dataset, high expression of miR-105-5p was associated with unfavourable OS in the validation cohort (HR: 1.53; 95% CI: 1–2.3; P value: 0.04) (Fig. 3e). PFS survival of miR-105-5p was not significant in the validation cohort (P value: 0.6).
Myeloma is a heterogenous cancer with large differences in survival between patients. Parameters for risk stratification include (R)-ISS staging, cytogenetics and other host factors (such as age). ISS staging combined with high-risk cytogenetics features /R-ISS is the standard system in routinely clinical use [1]. The implementation of chromosomal abnormalities in the ISS risk evaluation system has substantially improved the prediction of patient survival, but even within R-ISS subgroups there are further risk heterogeneity [7]. Identifying all high-risk myeloma patients is still a challenge and there is still room for improvement of the current stratification system. Precise risk prediction at diagnosis enables early intervention and opens for the use of risk-adapted treatment approaches and inclusion in clinical trials [35, 7].
In this study, we compared the expression of sRNAs in primary myeloma cells obtained from different disease stages and evaluated the association of sRNAs with patient prognosis. We found one miRNA, miR-105-5p to be an independent prognostic marker for poor OS in myeloma. sRNAs are promising biomarkers, predominantly studied in liquid biopsies [36]. With miRNAs as an exception [37], there is limited knowledge about this important group of non-coding RNAs in myeloma. The limited number of sRNA-seq studies may explain this knowledge gap. Previously, a sRNA-seq study focusing on miRNA and miRNA-offset-RNA was conducted on 30 myeloma patients [38]. MiRNA-offset-RNAs, which are stable, sRNA molecules with unknown functions transcribed from different miRNA loci [39], were found to associate with patient molecular subgroups in myeloma [38]. However, the characterisation of other sRNA species in the samples and how sRNA expression associated with survival were not investigated [38].
Here, using sRNA-seq, we identified snRNAs and miRNAs differentially expressed in disease stages of myeloma. With an exception for miR-873-5p, which was downregulated in Stage III compared to Stage I, expression of all the significant miRNAs, including let-7c-5p, miR-125-2-3p, miR-125b-5p, miR-3648, miR-3916, and miR-99a-5p was increased with increased severity of the disease. The U2 snRNAs, on the other hand, were downregulated in ISS III compared with ISS I, suggesting that reduction in mRNA splicing may be an oncogenic driver. None of the miRNAs and only some of the snRNAs that were associated with ISS stage are located within an annotated host gene. Moreover, those that were intragenic were not associated with ISS stage. This indicates that the differential expression of sRNA with ISS stage is not a direct effect of changes in host gene expression but may instead be directly related to their function in disease.
snRNAs have recently been identified as an important class of sRNAs that contributes to genome stability and in maintaining correct mRNA splicing [40]. The U2 snRNAs is a crucial component in the U2 small nuclear ribonucleoprotein, which is part of the spliceosome complex that remove introns from eukaryotic precursor mRNAs. The U2 snRNAs, which are important for both spliceosome assembly, intron substrate recognition and protein scaffolding are thought to play a role in cancer [41]. Knockdown experiments with snRNAs in breast cancer led to alternative splicing of genes frequently dysregulated in breast cancer, pointing towards a role of snRNAs as global gene regulators [22]. U2 knockdown primarily affected mRNA splice site recognition and exon inclusion [22]. The impact of U2 spliceosomal snRNAs expression has not previously been characterised in myeloma, but aberrant RNA splicing has recently been related to high-risk molecular subgroups and poor prognosis [42].
Previous miRNA studies that have investigated survival in myeloma have selected their miRNAs based on disease-related expression patterns such as differential expression in myeloma or between ISS stages, and subsequently evaluated their prognostic value. In our study, we identified all expressed miRNAs by sRNA-seq and evaluated their prognostic significance by discovery-based survival analysis, without a priori selection of specific miRNAs. A limitation of this study is the number of patients sequenced. Increasing the number of subjects would most likely increase the number of significant discoveries as many sRNAs were significantly associated with survival before adjusting for multiple testing.
Considering this, miR-105-5p stands out as a robust prognostic factor that predicts reduced survival, despite low N. Also, miR-105-5p significantly predicted survival in a multivariate model, indicating that it has an independent prognostic value. Finally, miR-105-5p is a prognostic marker in another, independent dataset, supporting the validity of our finding.
In our patient cohort the median OS time for patients with high miR-105-5p was 3.8 years, while for the patients with low miR-105-5p median survival was 9.07 year, thus miR-105-5p can be used to distinguish high-risk patients from low-risk patients. Furthermore, within the ISS III patient group, high miR-105-5p expressors had significantly worse outcome compared to low miR-105-5p expressors, suggesting that miR-105-5p may be used for further discrimination of patients in the high-risk subgroup. Patients with ISS III and high miR-105-5p had a median OS of 2.2 years while patients with ISS III and low miR-105-5p that had a median OS of 6.8 years, thus miR-105-5p may be a marker that can further stratify ultra-high-risk [43] patients from the other high-risk patients. Our dataset includes patients diagnosed in the years 2012–2017, and t(14;16) and LDH measurements were not available for the majority of patients. Thus, the patient's disease stage is therefore based on the "original" and not the R-ISS system, which limits the possibility of investigating miR-105-5p with respect to the R-ISS.
In summary, we provide a comprehensive characterisation of sRNAs in primary cells from myeloma patients and identify U2 spliceosomal snRNAs and miR-105-5p as novel potential biomarkers for disease stage and patient survival, respectively. The prognostic value of miR-105-5p was validated in an independent dataset, and we suggest further evaluation of miR-105-5p as a stratification parameter in future studies on myeloma patients to determine the clinical relevance as a biomarker for high-risk disease. Our study also warrants further investigation of the functional roles of U2 spliceosomal snRNAs and miR-105-5p in the pathogenesis of multiple myeloma.
The sRNA data and a comprehensive set of clinical data are available through an interactive web application, on which additional associations can be investigated (https://github.com/MjelleLab/MicroRNA-and-Gene-Expression-In-Multiple-Myeloma). The processed count matrices for all RNA classes, as well as the clinical data, are available on the same site. mRNA-miRNA, mRNA-clinical associations can also be assessed, as we have mRNA-seq data from the same samples [25]. Due to Norwegian law on sensitive data, raw data cannot be submitted to public repositories, however, all raw data are available upon request to the corresponding author.
The R code for statistical analysis is found in the supplemental information.
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We thank Biobank1 at St. Olavs Hospital for providing patient samples. We thank the Genomics Core Facility at the Norwegian University of Science and Technology (NTNU) for performing sequencing.
This work was supported by funds from the Norwegian Cancer Society (#206643,# 191861), the Research Council of Norway (#223255), the Liaison Committee for education, research and innovation in Central Norway (# 90061000 and #30171600) and the Cancer Fund at St. Olavs Hospital, Trondheim, Norway.
These authors jointly supervised this work: Therese Standal, Robin Mjelle.
Centre of Molecular Inflammation Research, Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, 7491, Trondheim, Norway
Kristin Roseth Aass, Tonje Marie Vikene Nedal, Synne Stokke Tryggestad & Therese Standal
Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, 7491, Trondheim, Norway
Kristin Roseth Aass, Tonje Marie Vikene Nedal, Siri Anshushaug Bouma, Synne Stokke Tryggestad, Tobias Schmidt Slørdahl, Anders Waage, Therese Standal & Robin Mjelle
Department of Hematology, Stavanger University Hospital, 4011, Stavanger, Norway
Einar Haukås
Department of Hematology, St. Olavs University Hospital, 7030, Trondheim, Norway
Tobias Schmidt Slørdahl, Anders Waage & Therese Standal
Bioinformatics Core Facility—BioCore, Norwegian University of Science and Technology NTNU, 7491, Trondheim, Norway
Robin Mjelle
Department of Pathology, St. Olavs University Hospital, 7030, Trondheim, Norway
Kristin Roseth Aass
Tonje Marie Vikene Nedal
Siri Anshushaug Bouma
Synne Stokke Tryggestad
Tobias Schmidt Slørdahl
Anders Waage
Therese Standal
KRA: prepared sequencing libraries, manuscript preparation and designed the study; TMVN: in vitro experiments, manuscript preparation; SAB: retrieved the clinical data; SST: in vitro experiments, EH: retrieved clinical data; TSS: retrieved the clinical data; AW: retrieved clinical data and manuscript preparation; TS: designed study, received funding and manuscript preparation; RM: data analysis and manuscript preparation.
Correspondence to Therese Standal or Robin Mjelle.
All patient samples were donated after informed consent, and the study was approved by the regional ethics committee (REK2011/2029 and 2012/2033). The study was performed in accordance with the Helsinki Declaration.
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Supplementary Figure 1
Supplementary Table 1
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Roseth Aass, K., Nedal, T.M.V., Anshushaug Bouma, S. et al. Comprehensive small RNA-sequencing of primary myeloma cells identifies miR-105-5p as a predictor of patient survival. Br J Cancer (2022). https://doi.org/10.1038/s41416-022-02065-1
Revised: 09 November 2022
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British Journal of Cancer (Br J Cancer) ISSN 1532-1827 (online) ISSN 0007-0920 (print)