Jinge Tian, Chenglong Wang, Fengyi Chen, Wenchao Qin, Hong Yang, Sihang Zhao, Jinliang Xia, Xian Du, Yifan Zhu, Lishuan Wu, Yan Cao, Hong Li, Junhong Zhuang, Shaojiang Chen, Huayuan Zhang, Qiuyue Chen, Mingcai Zhang, Xing Wang Deng, Dezhi Deng, Jigang Li, Feng Tian <<<

Increasing planting density is a key strategy to enhance maize yields. An ideotype for dense planting requires a 'smart canopy' with leaf angles at different canopy layers differentially optimized to maximize light interception and photosynthesis, amongst other features. Here, we identified leaf angle architecture of smart canopy 1 (lac1), a natural mutant possessing upright upper leaves, less erect middle leaves and relatively flat lower leaves. lac1 has improved photosynthetic capacity and weakened shade-avoidance responses under dense planting. lac1 encodes a brassinosteroid C-22 hydroxylase that predominantly regulates upper leaf angle. Phytochrome A photoreceptors accumulate in shade and interact with the transcription factor RAVL1 to promote its degradation via the 26S proteasome, thereby attenuating RAVL1 activation of lac1 and reducing brassinosteroid levels. This ultimately decreases upper leaf angle in dense fields. Large-scale field trials demonstrate lac1 boosts maize yields under high densities. To quickly introduce lac1 into breeding germplasm, we transformed a haploid inducer and recovered homozygous lac1 edits from 20 diverse inbred lines. The tested doubled haploids uniformly acquired smart-canopy-like plant architecture. We provide an important target and an accelerated strategy for developing high-density-tolerant cultivars, with lac1 serving as a genetic chassis for further engineering of a smart canopy in maize. <<<

Kathie Y Sun, Xiaodong Bai, Siying Chen, Suying Bao, Chuanyi Zhang, Manav Kapoor, Joshua Backman, Tyler Joseph, Evan Maxwell, George Mitra, Alexander Gorovits, Adam Mansfield, Boris Boutkov, Sujit Gokhale, Lukas Habegger, Anthony Marcketta, Adam E Locke, Liron Ganel, Alicia Hawes, Michael D Kessler, Deepika Sharma, Jeffrey Staples, Jonas Bovijn, Sahar Gelfman, Alessandro Di Gioia, Veera M Rajagopal, Alexander Lopez, Jennifer Rico Varela, Jesús Alegre-Díaz, Jaime Berumen, Roberto Tapia-Conyer, Pablo Kuri-Morales, Jason Torres, Jonathan Emberson, Rory Collins, Regeneron Genetics Center, RGC-ME Cohort Partners, Michael Cantor, Timothy Thornton, Hyun Min Kang, John D Overton, Alan R Shuldiner, M Laura Cremona, Mona Nafde, Aris Baras, Gonçalo Abecasis, Jonathan Marchini, Jeffrey G Reid, William Salerno, Suganthi Balasubramanian <<<

Rare coding variants that substantially affect function provide insights into the biology of a gene. However, ascertaining the frequency of such variants requires large sample sizes. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser. <<<

Christina V Theodoris, Ling Xiao, Anant Chopra, Mark D Chaffin, Zeina R Al Sayed, Matthew C Hill, Helene Mantineo, Elizabeth M Brydon, Zexian Zeng, X Shirley Liu, Patrick T Ellinor <<<

Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding and computer vision by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. During pretraining, Geneformer gained a fundamental understanding of network dynamics, encoding network hierarchy in the attention weights of the model in a completely self-supervised manner. Fine-tuning towards a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data demonstrated that Geneformer consistently boosted predictive accuracy. Applied to disease modelling with limited patient data, Geneformer identified candidate therapeutic targets for cardiomyopathy. Overall, Geneformer represents a pretrained deep learning model from which fine-tuning towards a broad range of downstream applications can be pursued to accelerate discovery of key network regulators and candidate therapeutic targets. <<<

Mathias Munschauer, Celina T Nguyen, Klara Sirokman, Christina R Hartigan, Larson Hogstrom, Jesse M Engreitz, Jacob C Ulirsch, Charles P Fulco, Vidya Subramanian, Jenny Chen, Monica Schenone, Mitchell Guttman, Steven A Carr, Eric S Lander <<<

The human genome contains thousands of long non-coding RNAs, but specific biological functions and biochemical mechanisms have been discovered for only about a dozen. A specific long non-coding RNA-non-coding RNA activated by DNA damage (NORAD)-has recently been shown to be required for maintaining genomic stability, but its molecular mechanism is unknown. Here we combine RNA antisense purification and quantitative mass spectrometry to identify proteins that directly interact with NORAD in living cells. We show that NORAD interacts with proteins involved in DNA replication and repair in steady-state cells and localizes to the nucleus upon stimulation with replication stress or DNA damage. In particular, NORAD interacts with RBMX, a component of the DNA-damage response, and contains the strongest RBMX-binding site in the transcriptome. We demonstrate that NORAD controls the ability of RBMX to assemble a ribonucleoprotein complex-which we term NORAD-activated ribonucleoprotein complex 1 (NARC1)-that contains the known suppressors of genomic instability topoisomerase I (TOP1), ALYREF and the PRPF19-CDC5L complex. Cells depleted for NORAD or RBMX display an increased frequency of chromosome segregation defects, reduced replication-fork velocity and altered cell-cycle progression-which represent phenotypes that are mechanistically linked to TOP1 and PRPF19-CDC5L function. Expression of NORAD in trans can rescue defects caused by NORAD depletion, but rescue is significantly impaired when the RBMX-binding site in NORAD is deleted. Our results demonstrate that the interaction between NORAD and RBMX is important for NORAD function, and that NORAD is required for the assembly of the previously unknown topoisomerase complex NARC1, which contributes to maintaining genomic stability. In addition, we uncover a previously unknown function for long non-coding RNAs in modulating the ability of an RNA-binding protein to assemble a higher-order ribonucleoprotein complex. <<<

Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning, owing to their reputed difficulty among the world's best talents in pre-university mathematics. Current machine-learning approaches, however, are not applicable to most mathematical domains owing to the high cost of translating human proofs into machine-verifiable format. The problem is even worse for geometry because of its unique translation challenges, resulting in severe scarcity of training data. We propose AlphaGeometry, a theorem prover for Euclidean plane geometry that sidesteps the need for human demonstrations by synthesizing millions of theorems and proofs across different levels of complexity. AlphaGeometry is a neuro-symbolic system that uses a neural language model, trained from scratch on our large-scale synthetic data, to guide a symbolic deduction engine through infinite branching points in challenging problems. On a test set of 30 latest olympiad-level problems, AlphaGeometry solves 25, outperforming the previous best method that only solves ten problems and approaching the performance of an average International Mathematical Olympiad (IMO) gold medallist. Notably, AlphaGeometry produces human-readable proofs, solves all geometry problems in the IMO 2000 and 2015 under human expert evaluation and discovers a generalized version of a translated IMO theorem in 2004. <<<

Francis R. Willett, Erin M. Kunz, Chaofei Fan, Donald T. Avansino, Guy H. Wilson, Eun Young Choi, Foram Kamdar, Matthew F. Glasser, Leigh R. Hochberg, Shaul Druckmann, Krishna V. Shenoy, Jaimie M. Henderson <<<

AbstractSpeech brain–computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1–7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant—who can no longer speak intelligibly owing to amyotrophic lateral sclerosis—achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI2) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant’s attempted speech was decoded at 62 words per minute, which is 3.4 times as fast as the previous record8 and begins to approach the speed of natural conversation (160 words per minute9). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak. <<<

Joe Nassour, Lucia Gutierrez Aguiar, Adriana Correia, Tobias T Schmidt, Laura Mainz, Sara Przetocka, Candy Haggblom, Nimesha Tadepalle, April Williams, Maxim N Shokhirev, Semih C Akincilar, Vinay Tergaonkar, Gerald S Shadel, Jan Karlseder <<<

Cancers arise through the accumulation of genetic and epigenetic alterations that enable cells to evade telomere-based proliferative barriers and achieve immortality. One such barrier is replicative crisis-an autophagy-dependent program that eliminates checkpoint-deficient cells with unstable telomeres and other cancer-relevant chromosomal aberrations. However, little is known about the molecular events that regulate the onset of this important tumour-suppressive barrier. Here we identified the innate immune sensor Z-DNA binding protein 1 (ZBP1) as a regulator of the crisis program. A crisis-associated isoform of ZBP1 is induced by the cGAS-STING DNA-sensing pathway, but reaches full activation only when associated with telomeric-repeat-containing RNA (TERRA) transcripts that are synthesized from dysfunctional telomeres. TERRA-bound ZBP1 oligomerizes into filaments on the outer mitochondrial membrane of a subset of mitochondria, where it activates the innate immune adapter protein mitochondrial antiviral-signalling protein (MAVS). We propose that these oligomerization properties of ZBP1 serve as a signal amplification mechanism, where few TERRA-ZBP1 interactions are sufficient to launch a detrimental MAVS-dependent interferon response. Our study reveals a mechanism for telomere-mediated tumour suppression, whereby dysfunctional telomeres activate innate immune responses through mitochondrial TERRA-ZBP1 complexes to eliminate cells destined for neoplastic transformation. <<<

Danillo G Augusto, Lawton D Murdolo, Demetra S M Chatzileontiadou, Joseph J Sabatino, Tasneem Yusufali, Noah D Peyser, Xochitl Butcher, Kerry Kizer, Karoline Guthrie, Victoria W Murray, Vivian Pae, Sannidhi Sarvadhavabhatla, Fiona Beltran, Gurjot S Gill, Kara L Lynch, Cassandra Yun, Colin T Maguire, Michael J Peluso, Rebecca Hoh, Timothy J Henrich, Steven G Deeks, Michelle Davidson, Scott Lu, Sarah A Goldberg, J Daniel Kelly, Jeffrey N Martin, Cynthia A Vierra-Green, Stephen R Spellman, David J Langton, Michael J Dewar-Oldis, Corey Smith, Peter J Barnard, Sulggi Lee, Gregory M Marcus, Jeffrey E Olgin, Mark J Pletcher, Martin Maiers, Stephanie Gras, Jill A Hollenbach <<<

Studies have demonstrated that at least 20% of individuals infected with SARS-CoV-2 remain asymptomatic. Although most global efforts have focused on severe illness in COVID-19, examining asymptomatic infection provides a unique opportunity to consider early immunological features that promote rapid viral clearance. Here, postulating that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection, we enrolled 29,947 individuals, for whom high-resolution HLA genotyping data were available, in a smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n = 1,428) comprised unvaccinated individuals who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci with disease course and identified a strong association between HLA-B*15:01 and asymptomatic infection, observed in two independent cohorts. Suggesting that this genetic association is due to pre-existing T cell immunity, we show that T cells from pre-pandemic samples from individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF. The majority of the reactive T cells displayed a memory phenotype, were highly polyfunctional and were cross-reactive to a peptide derived from seasonal coronaviruses. The crystal structure of HLA-B*15:01-peptide complexes demonstrates that the peptides NQKLIANQF and NQKLIANAF (from OC43-CoV and HKU1-CoV) share a similar ability to be stabilized and presented by HLA-B*15:01. Finally, we show that the structural similarity of the peptides underpins T cell cross-reactivity of high-affinity public T cell receptors, providing the molecular basis for HLA-B*15:01-mediated pre-existing immunity. <<<

Yingjie Bian, Wei Li, Daniel M Kremer, Peter Sajjakulnukit, Shasha Li, Joel Crespo, Zeribe C Nwosu, Li Zhang, Arkadiusz Czerwonka, Anna Pawłowska, Houjun Xia, Jing Li, Peng Liao, Jiali Yu, Linda Vatan, Wojciech Szeliga, Shuang Wei, Sara Grove, J Rebecca Liu, Karen McLean, Marcin Cieslik, Arul M Chinnaiyan, Witold Zgodziński, Grzegorz Wallner, Iwona Wertel, Karolina Okła, Ilona Kryczek, Costas A Lyssiotis, Weiping Zou <<<

Abnormal epigenetic patterns correlate with effector T cell malfunction in tumours, but the cause of this link is unknown. Here we show that tumour cells disrupt methionine metabolism in CD8 T cells, thereby lowering intracellular levels of methionine and the methyl donor S-adenosylmethionine (SAM) and resulting in loss of dimethylation at lysine 79 of histone H3 (H3K79me2). Loss of H3K79me2 led to low expression of STAT5 and impaired T cell immunity. Mechanistically, tumour cells avidly consumed methionine and outcompeted T cells for methionine by expressing high levels of the methionine transporter SLC43A2. Genetic and biochemical inhibition of tumour SLC43A2 restored H3K79me2 in T cells, thereby boosting spontaneous and checkpoint-induced tumour immunity. Moreover, methionine supplementation improved the expression of H3K79me2 and STAT5 in T cells, and this was accompanied by increased T cell immunity in tumour-bearing mice and patients with colon cancer. Clinically, tumour SLC43A2 correlated negatively with T cell histone methylation and functional gene signatures. Our results identify a mechanistic connection between methionine metabolism, histone patterns, and T cell immunity in the tumour microenvironment. Thus, cancer methionine consumption is an immune evasion mechanism, and targeting cancer methionine signalling may provide an immunotherapeutic approach. <<<

Chaoxiong Wang, Xichen Zheng, Jinlan Zhang, Xiaoyi Jiang, Jia Wang, Yuwei Li, Xiaonan Li, Guanghui Shen, Jiayin Peng, Peixuan Zheng, Yunqing Gu, Jiaojiao Chen, Moubin Lin, Changwen Deng, Hai Gao, Zhigang Lu, Yun Zhao, Min Luo <<<

The immune-suppressive tumour microenvironment represents a major obstacle to effective immunotherapy. Pathologically activated neutrophils, also known as polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), are a critical component of the tumour microenvironment and have crucial roles in tumour progression and therapy resistance. Identification of the key molecules on PMN-MDSCs is required to selectively target these cells for tumour treatment. Here, we performed an in vivo CRISPR-Cas9 screen in a tumour mouse model and identified CD300ld as a top candidate of tumour-favouring receptors. CD300ld is specifically expressed in normal neutrophils and is upregulated in PMN-MDSCs upon tumour-bearing. CD300ld knockout inhibits the development of multiple tumour types in a PMN-MDSC-dependent manner. CD300ld is required for the recruitment of PMN-MDSCs into tumours and their function to suppress T cell activation. CD300ld acts via the STAT3-S100A8/A9 axis, and knockout of Cd300ld reverses the tumour immune-suppressive microenvironment. CD300ld is upregulated in human cancers and shows an unfavourable correlation with patient survival. Blocking CD300ld activity inhibits tumour development and has synergistic effects with anti-PD1. Our study identifies CD300ld as a critical immune suppressor present on PMN-MDSCs, being required for tumour immune resistance and providing a potential target for cancer immunotherapy. <<<

Wen-Wei Liao, Mobin Asri, Jana Ebler, Daniel Doerr, Marina Haukness, Glenn Hickey, Shuangjia Lu, Julian K Lucas, Jean Monlong, Haley J Abel, Silvia Buonaiuto, Xian H Chang, Haoyu Cheng, Justin Chu, Vincenza Colonna, Jordan M Eizenga, Xiaowen Feng, Christian Fischer, Robert S Fulton, Shilpa Garg, Cristian Groza, Andrea Guarracino, William T Harvey, Simon Heumos, Kerstin Howe, Miten Jain, Tsung-Yu Lu, Charles Markello, Fergal J Martin, Matthew W Mitchell, Katherine M Munson, Moses Njagi Mwaniki, Adam M Novak, Hugh E Olsen, Trevor Pesout, David Porubsky, Pjotr Prins, Jonas A Sibbesen, Jouni Sirén, Chad Tomlinson, Flavia Villani, Mitchell R Vollger, Lucinda L Antonacci-Fulton, Gunjan Baid, Carl A Baker, Anastasiya Belyaeva, Konstantinos Billis, Andrew Carroll, Pi-Chuan Chang, Sarah Cody, Daniel E Cook, Robert M Cook-Deegan, Omar E Cornejo, Mark Diekhans, Peter Ebert, Susan Fairley, Olivier Fedrigo, Adam L Felsenfeld, Giulio Formenti, Adam Frankish, Yan Gao, Nanibaa' A Garrison, Carlos Garcia Giron, Richard E Green, Leanne Haggerty, Kendra Hoekzema, Thibaut Hourlier, Hanlee P Ji, Eimear E Kenny, Barbara A Koenig, Alexey Kolesnikov, Jan O Korbel, Jennifer Kordosky, Sergey Koren, HoJoon Lee, Alexandra P Lewis, Hugo Magalhães, Santiago Marco-Sola, Pierre Marijon, Ann McCartney, Jennifer McDaniel, Jacquelyn Mountcastle, Maria Nattestad, Sergey Nurk, Nathan D Olson, Alice B Popejoy, Daniela Puiu, Mikko Rautiainen, Allison A Regier, Arang Rhie, Samuel Sacco, Ashley D Sanders, Valerie A Schneider, Baergen I Schultz, Kishwar Shafin, Michael W Smith, Heidi J Sofia, Ahmad N Abou Tayoun, Françoise Thibaud-Nissen, Francesca Floriana Tricomi, Justin Wagner, Brian Walenz, Jonathan M D Wood, Aleksey V Zimin, Guillaume Bourque, Mark J P Chaisson, Paul Flicek, Adam M Phillippy, Justin M Zook, Evan E Eichler, David Haussler, Ting Wang, Erich D Jarvis, Karen H Miga, Erik Garrison, Tobias Marschall, Ira M Hall, Heng Li, Benedict Paten <<<

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample. <<<

Jun Li, Melissa J Hubisz, Ethan M Earlie, Mercedes A Duran, Christy Hong, Austin A Varela, Emanuele Lettera, Matthew Deyell, Bernardo Tavora, Jonathan J Havel, Su M Phyu, Amit Dipak Amin, Karolina Budre, Erina Kamiya, Julie-Ann Cavallo, Christopher Garris, Simon Powell, Jorge S Reis-Filho, Hannah Wen, Sarah Bettigole, Atif J Khan, Benjamin Izar, Eileen E Parkes, Ashley M Laughney, Samuel F Bakhoum <<<

Chromosomal instability (CIN) is a driver of cancer metastasis, yet the extent to which this effect depends on the immune system remains unknown. Using ContactTracing-a newly developed, validated and benchmarked tool to infer the nature and conditional dependence of cell-cell interactions from single-cell transcriptomic data-we show that CIN-induced chronic activation of the cGAS-STING pathway promotes downstream signal re-wiring in cancer cells, leading to a pro-metastatic tumour microenvironment. This re-wiring is manifested by type I interferon tachyphylaxis selectively downstream of STING and a corresponding increase in cancer cell-derived endoplasmic reticulum (ER) stress response. Reversal of CIN, depletion of cancer cell STING or inhibition of ER stress response signalling abrogates CIN-dependent effects on the tumour microenvironment and suppresses metastasis in immune competent, but not severely immune compromised, settings. Treatment with STING inhibitors reduces CIN-driven metastasis in melanoma, breast and colorectal cancers in a manner dependent on tumour cell-intrinsic STING. Finally, we show that CIN and pervasive cGAS activation in micronuclei are associated with ER stress signalling, immune suppression and metastasis in human triple-negative breast cancer, highlighting a viable strategy to identify and therapeutically intervene in tumours spurred by CIN-induced inflammation. <<<

Ana Luísa Correia, Joao C Guimaraes, Priska Auf der Maur, Duvini De Silva, Marcel P Trefny, Ryoko Okamoto, Sandro Bruno, Alexander Schmidt, Kirsten Mertz, Katrin Volkmann, Luigi Terracciano, Alfred Zippelius, Marcus Vetter, Christian Kurzeder, Walter Paul Weber, Mohamed Bentires-Alj <<<

The persistence of undetectable disseminated tumour cells (DTCs) after primary tumour resection poses a major challenge to effective cancer treatment. These enduring dormant DTCs are seeds of future metastases, and the mechanisms that switch them from dormancy to outgrowth require definition. Because cancer dormancy provides a unique therapeutic window for preventing metastatic disease, a comprehensive understanding of the distribution, composition and dynamics of reservoirs of dormant DTCs is imperative. Here we show that different tissue-specific microenvironments restrain or allow the progression of breast cancer in the liver-a frequent site of metastasis that is often associated with a poor prognosis. Using mouse models, we show that there is a selective increase in natural killer (NK) cells in the dormant milieu. Adjuvant interleukin-15-based immunotherapy ensures an abundant pool of NK cells that sustains dormancy through interferon-γ signalling, thereby preventing hepatic metastases and prolonging survival. Exit from dormancy follows a marked contraction of the NK cell compartment and the concurrent accumulation of activated hepatic stellate cells (aHSCs). Our proteomics studies on liver co-cultures implicate the aHSC-secreted chemokine CXCL12 in the induction of NK cell quiescence through its cognate receptor CXCR4. CXCL12 expression and aHSC abundance are closely correlated in patients with liver metastases. Our data identify the interplay between NK cells and aHSCs as a master switch of cancer dormancy, and suggest that therapies aimed at normalizing the NK cell pool might succeed in preventing metastatic outgrowth. <<<

Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Abubakr Babiker, Nathanael Schärli, Aakanksha Chowdhery, Philip Mansfield, Dina Demner-Fushman, Blaise Agüera Y Arcas, Dale Webster, Greg S Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan <<<

Large language models (LLMs) have demonstrated impressive capabilities, but the bar for clinical applications is high. Attempts to assess the clinical knowledge of models typically rely on automated evaluations based on limited benchmarks. Here, to address these limitations, we present MultiMedQA, a benchmark combining six existing medical question answering datasets spanning professional medicine, research and consumer queries and a new dataset of medical questions searched online, HealthSearchQA. We propose a human evaluation framework for model answers along multiple axes including factuality, comprehension, reasoning, possible harm and bias. In addition, we evaluate Pathways Language Model (PaLM, a 540-billion parameter LLM) and its instruction-tuned variant, Flan-PaLM on MultiMedQA. Using a combination of prompting strategies, Flan-PaLM achieves state-of-the-art accuracy on every MultiMedQA multiple-choice dataset (MedQA, MedMCQA, PubMedQA and Measuring Massive Multitask Language Understanding (MMLU) clinical topics), including 67.6% accuracy on MedQA (US Medical Licensing Exam-style questions), surpassing the prior state of the art by more than 17%. However, human evaluation reveals key gaps. To resolve this, we introduce instruction prompt tuning, a parameter-efficient approach for aligning LLMs to new domains using a few exemplars. The resulting model, Med-PaLM, performs encouragingly, but remains inferior to clinicians. We show that comprehension, knowledge recall and reasoning improve with model scale and instruction prompt tuning, suggesting the potential utility of LLMs in medicine. Our human evaluations reveal limitations of today's models, reinforcing the importance of both evaluation frameworks and method development in creating safe, helpful LLMs for clinical applications. <<<

Avishai Gavish, Michael Tyler, Alissa C Greenwald, Rouven Hoefflin, Dor Simkin, Roi Tschernichovsky, Noam Galili Darnell, Einav Somech, Chaya Barbolin, Tomer Antman, Daniel Kovarsky, Thomas Barrett, L Nicolas Gonzalez Castro, Debdatta Halder, Rony Chanoch-Myers, Julie Laffy, Michael Mints, Adi Wider, Rotem Tal, Avishay Spitzer, Toshiro Hara, Maria Raitses-Gurevich, Chani Stossel, Talia Golan, Amit Tirosh, Mario L Suvà, Sidharth V Puram, Itay Tirosh <<<

Each tumour contains diverse cellular states that underlie intratumour heterogeneity (ITH), a central challenge of cancer therapeutics. Dozens of recent studies have begun to describe ITH by single-cell RNA sequencing, but each study typically profiled only a small number of tumours and provided a narrow view of transcriptional ITH. Here we curate, annotate and integrate the data from 77 different studies to reveal the patterns of transcriptional ITH across 1,163 tumour samples covering 24 tumour types. Among the malignant cells, we identify 41 consensus meta-programs, each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumours. The meta-programs cover diverse cellular processes including both generic (for example, cell cycle and stress) and lineage-specific patterns that we map into 11 hallmarks of transcriptional ITH. Most meta-programs of carcinoma cells are similar to those identified in non-malignant epithelial cells, suggesting that a large fraction of malignant ITH programs are variable even before oncogenesis, reflecting the biology of their cell of origin. We further extended the meta-program analysis to six common non-malignant cell types and utilize these to map cell-cell interactions within the tumour microenvironment. In summary, we have assembled a comprehensive pan-cancer single-cell RNA-sequencing dataset, which is available through the Curated Cancer Cell Atlas website, and leveraged this dataset to carry out a systematic characterization of transcriptional ITH. <<<

Johann S Bergholz, Qiwei Wang, Qi Wang, Michelle Ramseier, Sanjay Prakadan, Weihua Wang, Rong Fang, Sheheryar Kabraji, Qian Zhou, G Kenneth Gray, Kayley Abell-Hart, Shaozhen Xie, Xiaocan Guo, Hao Gu, Thanh Von, Tao Jiang, Shuang Tang, Gordon J Freeman, Hye-Jung Kim, Alex K Shalek, Thomas M Roberts, Jean J Zhao <<<

Loss of the PTEN tumour suppressor is one of the most common oncogenic drivers across all cancer types. PTEN is the major negative regulator of PI3K signalling. The PI3Kβ isoform has been shown to play an important role in PTEN-deficient tumours, but the mechanisms underlying the importance of PI3Kβ activity remain elusive. Here, using a syngeneic genetically engineered mouse model of invasive breast cancer driven by ablation of both Pten and Trp53 (which encodes p53), we show that genetic inactivation of PI3Kβ led to a robust anti-tumour immune response that abrogated tumour growth in syngeneic immunocompetent mice, but not in immunodeficient mice. Mechanistically, PI3Kβ inactivation in the PTEN-null setting led to reduced STAT3 signalling and increased the expression of immune stimulatory molecules, thereby promoting anti-tumour immune responses. Pharmacological PI3Kβ inhibition also elicited anti-tumour immunity and synergized with immunotherapy to inhibit tumour growth. Mice with complete responses to the combined treatment displayed immune memory and rejected tumours upon re-challenge. Our findings demonstrate a molecular mechanism linking PTEN loss and STAT3 activation in cancer and suggest that PI3Kβ controls immune escape in PTEN-null tumours, providing a rationale for combining PI3Kβ inhibitors with immunotherapy for the treatment of PTEN-deficient breast cancer. <<<