Passenger Genes Research Articles

Arginines of the CGN codon family are Achilles' heels of cancer genes.

Recent studies have revealed that arginine is the most favorable target of amino acid alteration in most cancer types and it has been suggested that the high preference for arginine mutations reflects the critical roles of this amino acid in the function of proteins. High rates of mutations of arginine residues in cancer, however, might also be due to increased mutability of arginine codons of the CGN family as the CpG dinucleotides of these codons may be methylated. In the present work we have analyzed spectra of single base substitutions of cancer genes (oncogenes, tumor suppressor genes) and passenger genes in cancer tissues to assess the contributions of CpG hypermutability and selection to arginine mutations. Our studies have shown that arginines encoded by the CGN codon family display higher rates of mutation in both cancer genes and passenger genes than arginine codons AGA and AGG that are devoid of CpG dinucleotide, suggesting that the predominance of arginine mutations in cancer is primarily due to CpG hypermutability, rather than selection for arginine replacement. Nevertheless, our results also suggest that CGN codons for arginines may serve as Achilles' heels of cancer genes. CpG hypermutability of key arginines of proto-oncogenes, leading to high rates of recurrence of driver mutations, contributes significantly to carcinogenesis. Similarly, our results indicate that hypermutability of the CpG dinucleotide of CGA codons (converting them to TGA stop codons) contributes significantly to recurrent truncation and inactivation of tumor suppressor genes.

Abstract 3364: PELO is a synthetic lethal target in chromosome 9p21-deleted or MSI cancers

Abstract Homozygous deletion of chromosomal region 9p21.3 is one of the most frequently observed somatic copy number alterations in cancers, occurring in approximately 15% of all cancers. Many of the 9p21.3-deleted cancers are further characterized by poor clinical outcomes including subsets of glioblastoma, pancreatic, esophageal, and urothelial cancers. Large deletions of chromosomal regions may also provide unique therapeutic opportunities. Specifically, cancer-specific therapeutic opportunities can arise from co-deletions of passenger genes neighboring tumor suppressors. As such, we sought to identify novel therapeutic targets associated with Ch9p21.3 loss in cancers and identified the pelota mRNA surveillance and ribosome rescue factor (PELO) as the top preferential dependency in 9p21.3-deleted cancers. Intriguingly in another analysis, we identified PELO to be amongst the top preferential dependencies in cancers with microsatellite instability (MSI), which accounts for subsets of colorectal, endometrial, gastric, and ovarian cancers. Given the strength of PELO as a candidate synthetic lethal target in two distinct cancer subsets, we performed focused validation with CRISPR interference across multiple cell lines. Knockdown of PELO preferentially impaired the viability of MSI or 9p21-deleted as compared to control (9p21-proficient and microsatellite stable) cells. Further validation with patient-derived organoid and in vivo xenograft models confirmed these findings. We next sought to refine the predictive biomarkers for PELO dependency and identified loss of FOCAD (a 9p21.3 gene and an interactor of the SKI mRNA surveillance pathway) as necessary and sufficient for PELO dependency in the 9p21.3-deleted context. Our findings implicate splicing alterations involving TTC37, a key protein in the SKI mRNA surveillance complex, as the underlying cause of PELO dependency in MSI cancers. Together, we found that loss of large deletions of 9p21.3 and MSI independently impair the SKI complex, uncovering a dependency upon PELO and highlighting a novel functional interaction between PELO and the SKI complex. Furthermore, the strength of this synthetic lethal interaction in a broad range of cancers with poor outcomes underscores the potential of PELO as a promising drug target for patients with 9p21.3-deleted or MSI cancers. Citation Format: Edmond M. Chan, Patricia Borck, Nolan Bick, Kristina Jankovic, Isabella Boyle, Lucy Parker-Burns, Kyla Foster, Anthony Lau, Ashir Borah, Joshua Dempster, Francisca Vazquez. PELO is a synthetic lethal target in chromosome 9p21-deleted or MSI cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3364.

Comparative Genome Analysis of Two Streptococcus suis Serotype 8 Strains Identifies Two New Virulence-Associated Genes.

Streptococcus suis is an important zoonotic pathogen that can cause meningitis and septicemia in swine and humans. Among numerous pathogenic serotypes, S. suis serotype 8 has distinctive characteristics such as a high detection rate and causing multi-host infection. There is no complete genome of serotype 8 strains so far. In this study, the complete genome of two S. suis serotype 8 strains, virulent strain 2018WUSS151 and non-virulent strain WUSS030, were sequenced. Comparative genomic analysis showed that the homology of the two genomes reaches 99.68%, and the main difference is the distinctive prophages. There are 83 genes unique to virulent strain 2018WUSS151, including three putative virulence-associated genes (PVGs). Two PVGs, padR and marR, are passenger genes in ISSsu2 family transposons that are able to form circular DNA intermediates during transposition, indicating the possibility of horizontal transmission among S. suis strains. The deletion mutant of PVGs marR or atpase attenuated the virulence of serotype 2 virulent SC070731 in a mouse infection model, confirming their role in S. suis virulence. These findings contribute to clarifying the genomic characterization of S. suis serotype 8 and S. suis pathogenesis.

Abstract A005: Quantification of cancer effect sizes of somatic variants reveals stage-dependent evolution in primary and metastatic skin cutaneous melanoma

Abstract The identities of driver and passenger genes in skin cutaneous melanoma (SKCM) have been intensively studied. However, the relative enhancement of cancer cell lineage survival and proliferation by SKCM driver mutations, as well as how these cancer effects vary with cancer stage, remains limited. The cancer effect size (also known as the scaled selection coefficient) quantifies the relative cancer cell lineage survival and proliferation in the context of each driver mutation. Using a diverse set of 999 primary and 1149 metastatic SKCM samples from multiple datasets, including The Cancer Genome Atlas (TCGA) and the AACR Project GENIE, we computed the cancer effect size of all recurrent mutations in primary (Stage I–III) and metastatic (Stage IV) tumors. Our analysis revealed that both primary and metastatic tumors were alike in their trinucleotide mutation profiles. However, the underlying gene mutation rates typically increased from primary to metastatic tumors as the latter group typically features ineffective DNA repair machinery. Additionally, the two cohorts noticeably differed in both magnitudes of effect sizes and in which genes specific somatic variants were most highly selected. Effect sizes of several driver mutations, most notably BRAF V600E, were orders of magnitude higher in metastatic tumors than in primary tumors. Furthermore, certain variants, particularly NONO R184L, were highly selected along the trajectory from normal tissue to primary tumors, yet new mutations were no longer selected between primary tumor resection and the development of resectable metastases. Conversely, for several variants, including H3F3B R18L, TP53 R273L, and PIK3CA R115P, selection was very strong only along the trajectory from resectable primary tumors to metastases. These findings illustrate the shifting evolutionary trajectory of tumors across cancer stages, underscoring the importance of early detection of SKCM and informing the development of targeted therapeutics aimed at specific stages of tumorigenesis. Citation Format: Rishi M Shah, Moein Rajaei, Jeff Mandell, Jeffrey P Townsend. Quantification of cancer effect sizes of somatic variants reveals stage-dependent evolution in primary and metastatic skin cutaneous melanoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A005.

Conditional deletion of Ccl2 in smooth muscle cells does not reduce early atherosclerosis in mice

Background and aimsC–C motif chemokine ligand 2 (CCL2) is a pro-inflammatory chemokine important for monocyte recruitment to the arterial wall and atherosclerotic plaques. Global knockout of Ccl2 reduces plaque formation and macrophage content in mice, but the importance of different plaque cell types in mediating this effect has not been resolved. Smooth muscle cells (SMCs) can adopt a potentially pro-inflammatory function with expression of CCL2. The present study aimed to test the hypothesis that SMC-secreted CCL2 is involved in early atherogenesis in mice. MethodsSMC-restricted Cre recombinase was activated at 6 weeks of age in mice with homozygous floxed or wildtype Ccl2 alleles. Separate experiments in mice lacking the Cre recombinase transgene were conducted to control for genetic background effects. Hypercholesterolemia and atherosclerosis were induced by a tail vein injection of recombinant adeno-associated virus (rAAV) encoding proprotein convertase subtilisin/kexin type 9 (PCSK9) and a high-fat diet for 12 weeks. ResultsUnexpectedly, mice with SMC-specific Ccl2 deletion developed higher levels of plasma cholesterol and larger atherosclerotic plaques with more macrophages compared with wild-type littermates. When total cholesterol levels were incorporated into the statistical analysis, none of the effects on plaque development between groups remained significant. Importantly, changes in plasma cholesterol and atherosclerosis remained in mice lacking Cre recombinase indicating that they were not caused by SMC-specific CCL2 deletion but by effects of the floxed allele or passenger genes. ConclusionsSMC-specific deficiency of Ccl2 does not significantly affect early plaque development in hypercholesterolemic mice.

Prognostic potential of whole exome sequencing in the clinical management of metachronous colorectal cancer liver metastases

BackgroundColorectal cancer is a highly prevalent and deadly. The most common metastatic site is the liver. We performed a whole exome sequencing analysis of a series of metachronous colorectal cancer liver metastases (mCLM) and matched non-malignant liver tissues to investigate the genomic profile of mCLM and explore associations with the patients’ prognosis and therapeutic modalities.MethodsDNA samples from mCLM and non-malignant liver tissue pairs (n = 41) were sequenced using whole exome target enrichment and their germline and somatic genetic variability, copy number variations, and mutational signatures were assessed for associations with relapse-free (RFS) and overall survival (OS).ResultsOur genetic analysis could stratify all patients into existing targeted therapeutic regimens. The most commonly mutated genes in mCLM were TP53, APC, and KRAS together with PIK3CA and several passenger genes like ABCA13, FAT4, PCLO, and UNC80. Patients with somatic alterations in genes from homologous recombination repair, Notch, and Hedgehog pathways had significantly prolonged RFS, while those with altered MYC pathway genes had poor RFS. Additionally, alterations in the JAK-STAT pathway were prognostic of longer OS. Patients bearing somatic variants in VIPR2 had significantly shorter OS and those with alterations in MUC16 prolonged OS. Carriage of the KRAS-12D variant was associated with shortened survival in our and external datasets. On the other hand, tumor mutation burden, mismatch repair deficiency, microsatellite instability, mutational signatures, or copy number variation in mCLM had no prognostic value.ConclusionsThe results encourage further molecular profiling for personalized treatment of colorectal cancer liver metastases discerning metachronous from synchronous scenarios.

A Mouse-Specific Model to Detect Genes under Selection in Tumors.

The mouse is a widely used model organism in cancer research. However, no computational methods exist to identify cancer driver genes in mice due to a lack of labeled training data. To address this knowledge gap, we adapted the GUST (Genes Under Selection in Tumors) model, originally trained on human exomes, to mouse exomes via transfer learning. The resulting tool, called GUST-mouse, can estimate long-term and short-term evolutionary selection in mouse tumors, and distinguish between oncogenes, tumor suppressor genes, and passenger genes using high-throughput sequencing data. We applied GUST-mouse to analyze 65 exomes of mouse primary breast cancer models and 17 exomes of mouse leukemia models. Comparing the predictions between cancer types and between human and mouse tumors revealed common and unique driver genes. The GUST-mouse method is available as an open-source R package on github.

Label-free nLC-MS/MS proteomic analysis reveals significant differences in the proteome between colorectal cancer tissues and normal colon mucosa.

Despite the discovery of numerous driving and passenger genes that play key roles in cancer characteristics, progress in cancer treatment has not been satisfactory. This is mainly because conventional therapies are neither selective nor targeted. Another important reason is that cancer cells rapidly develop resistance to chemotherapeutic agents due to excessive accumulation of mutations and/or epigenetic changes. In light of this, we believe that the discovery of new targets and key genes/proteins could improve treatment options. In this study, tissue samples (tumor and normal mucosa) were first collected from the colon or rectum by right or left hemicolectomy. Proteomic analysis was then performed using the label-free nLC-MS/MS method. We determined 77 proteins with statistically significant differences in expression levels between cancerous and normal mucosa. While the expression of 76 proteins was decreased in cancer tissues, only one protein (RNA-binding motif protein_X chromosome-RBMX) was increased in colorectal cancer tissues. The bioinformatics portal Metascape was used to determine the biological processes involved. 77 proteins with significantly different expression between cancerous and normal tissues were compared with the UALCAN platform using data from the Clinical Proteomics Tumor Analysis Consortium (CPTAC). The results for 45 of the 77 proteins clearly matched the CPTAC dataset. Western blot studies confirmed that RBMX protein (critical for gene transcription and alternative splicing of various pre-mRNAs) was increased 2.04-fold, while decorin protein (a matrix proteoglycan with tumor suppressor functions) was dramatically decreased by about 6.04-fold in tumor samples compared with normal mucosa.

Bioinformatics analyses suggest that mutations in COL12A1 and its miRNAs promote stomach adenocarcinoma via loss of COL12A1 suppression

Abstract Objectives Stomach adenocarcinoma (STAD) is the fifth most common cancer and the third leading cause of cancer-related deaths worldwide. It is important to understand its molecular basis better and identify noninvasive biomarkers for targeted therapy. Usually, tumors contain driver genes or passenger genes, which can be regulated by microRNAs (miRNAs). However, the mechanism underlying the interaction between miRNA and their target genes in STAD has not been fully demonstrated. To date, no miRNA-targeted gene mutation sites that promote STAD progression have been reported, and there are no reports of the mutations within the 3′-UTR of COL12A1 that could contribute to STAD development. Methods Here, multiple genomic and transcriptomic profiles of STAD patients were downloaded from several reputable online databases and various analyses were conducted, including assessments of mutation rates, copy number variations (CNVs), single‐nucleotide polymorphisms (SNPs), RNA secondary structure, protein-protein interaction (PPI), pathway network, differentially expressed genes (DEGs), and patient survival rate. We aimed to evaluate impact of the SNPs on progression of stomach adenocarcinoma. Results We identified 22 critical DEGs involved in cell-cell and cell-matrix interaction. Seven of these key DEGs, including COL12A1, were associated with poorer overall survival. Interestingly, we found that COL12A1 was targeted by the miRNAs: hsa-miR-130b-5p (which carries the mutations rs1174814901 and rs761813865) and hsa-miR-18a-5p (which carries the mutation rs1198460870). These mutations lead to a change in the secondary structure of the miRNAs. And we also found that the miRNA target sites of COL12A1 were also mutated. These mutations at both miRNAs and COL12A1 likely attenuated their binding capability, leading to compensatory miRNA overexpression in the STAD patients. The miRNA overexpression was further found to be significantly associated with worse survival in STAD patients. Conclusions Our results suggest that mutations in Col12A1 and its miRNAs promote STAD via loss of COL12A1 suppression, providing new insight into the molecular mechanisms of STAD progression. This finding has significant implications for the development of novel noninvasive diagnostic, prognostic and therapeutic biomarkers.

Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures.

Epilepsy is a neurological disorder characterized by hypersynchronous recurrent neuronal activities and seizures, as well as loss of muscular control and sometimes awareness. Clinically, seizures have been reported to display daily variations. Conversely, circadian misalignment and circadian clock gene variants contribute to epileptic pathogenesis. Elucidation of the genetic bases of epilepsy is of great importance because the genetic variability of the patients affects the efficacies of antiepileptic drugs (AEDs). For this narrative review, we compiled 661 epilepsy-related genes from the PHGKB and OMIM databases and classified them into 3 groups: driver genes, passenger genes, and undetermined genes. We discuss the potential roles of some epilepsy driver genes based on GO and KEGG analyses, the circadian rhythmicity of human and animal epilepsies, and the mutual effects between epilepsy and sleep. We review the advantages and challenges of rodents and zebrafish as animal models for epileptic studies. Finally, we posit chronomodulated strategy-based chronotherapy for rhythmic epilepsies, integrating several lines of investigation for unraveling circadian mechanisms underpinning epileptogenesis, chronopharmacokinetic and chronopharmacodynamic examinations of AEDs, as well as mathematical/computational modeling to help develop time-of-day-specific AED dosing schedules for rhythmic epilepsy patients.

Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes

The colorectal cancer tumor microenvironment presents significant genetic heterogeneity with mutations in genes in several signaling pathways. Detecting these driver genes through wet lab experiments is costly and time-consuming. Computational models and bioinformatic tools have become a vital alternative in this effort. One of these novel computational methods, Centrality Analysis, models molecular functions, biological processes and biochemical pathways by creating and analyzing protein-protein interaction networks. Centrality Analysis is an approach to quantify node (in this case, protein) importance in these networks. Essential proteins play critical roles in cell function; therefore, centrality measures serve as a basis to study the relationship between lethality and essentiality by evaluating the topological features of the network. However, there is no established standard to determine the most appropriate centrality measure for analyzing a specific network. The choice of a suitable set is complicated by the impact of network topology because results vary based on network structure, correlation among the selected set of measures, and network data collection methods used. We hypothesized that centrality scores can be used to predict driver genes while statistical and machine learning analyses can identify the relevant centrality features for this task. We proposed different analyses to select a valid set of centrality algorithms to predict driver and non-driver genes. We first recreated a protein-protein interaction network for colorectal cancer featuring known driver and passenger genes, and then compared the centrality scores of eight different algorithms using statistical analysis. We further validated the results by implementing machine learning models. Both analyses identified betweenness and closeness centrality algorithms as most important to predict driver versus non-driver genes.

DriverMP enables improved identification of cancer driver genes.

Cancer is widely regarded as a complex disease primarily driven by genetic mutations. A critical concern and significant obstacle lies in discerning driver genes amid an extensive array of passenger genes. We present a new method termed DriverMP for effectively prioritizing altered genes on a cancer-type level by considering mutated gene pairs. It is designed to first apply nonsilent somatic mutation data, protein‒protein interaction network data, and differential gene expression data to prioritize mutated gene pairs, and then individual mutated genes are prioritized based on prioritized mutated gene pairs. Application of this method in 10 cancer datasets from The Cancer Genome Atlas demonstrated its great improvements over all the compared state-of-the-art methods in identifying known driver genes. Then, a comprehensive analysis demonstrated the reliability of the novel driver genes that are strongly supported by clinical experiments, disease enrichment, or biological pathway analysis. The new method, DriverMP, which is able to identify driver genes by effectively integrating the advantages of multiple kinds of cancer data, is available at https://github.com/LiuYangyangSDU/DriverMP. In addition, we have developed a novel driver gene database for 10 cancer types and an online service that can be freely accessed without registration for users. The DriverMP method, the database of novel drivers, and the user-friendly online server are expected to contribute to new diagnostic and therapeutic opportunities for cancers.

Somatic mutation distribution across tumour cohorts provides a signal for positive selection in cancer

Cancer gene discovery is reliant on distinguishing driver mutations from a multitude of passenger mutations in tumour genomes. While driver genes may be revealed based on excess mutation recurrence or clustering, there is a need for orthogonal principles. Here, we take advantage of the fact that non-cancer genes, containing only passenger mutations under neutral selection, exhibit a likelihood of mutagenesis in a given tumour determined by the tumour’s mutational signature and burden. This relationship can be disrupted by positive selection, leading to a difference in the distribution of mutated cases across a cohort for driver and passenger genes. We apply this principle to detect cancer drivers independently of recurrence in large pan-cancer cohorts, and show that our method (SEISMIC) performs comparably to traditional approaches and can provide resistance to known confounding mutational phenomena. Being based on a different principle, the approach provides a much-needed complement to existing methods for detecting signals of selection.

STEM-25. IN VIVO FUNCTIONAL GENOMICS IDENTIFIES ESSENTIALITY OF POTASSIUM HOMEOSTASIS IN MEDULLOBLASTOMA

Abstract Distinguishing cancer maintenance genes—i.e. genes essential and specific to tumor survival—from initiation, progression, and passenger genes is critical for developing effective cancer therapeutics. We engineered the Lazy Piggy genetic screening system, which uses a Sleeping Beauty / piggyBac hybrid transposon to dysregulate and later restore gene expression. In vivo spatiotemporal control of Lazy Piggy transposon insertion and remobilization depletes insertions that are non-essential for tumor survival while enriching for maintenance driver insertions. Using this functional genomic approach, we identify potassium channels as a regulator for medulloblastoma, the most common pediatric brain malignancy. Loss of potassium channel Kcnb2 diminishes the pool of medulloblastoma-propagating cells by hampering their replication potential, thereby prolonging the survival of tumor-bearing mice. Mechanistically, Kcnb2 governs potassium homeostasis to regulate plasma membrane tension-gated EGFR signaling, which drives the proliferative expansion of medulloblastoma-propagating cells. Our in vivo functional genomics reveals potassium homeostasis as a tumor maintenance essentiality, establishes a link between potassium channel activity and plasma membrane tension, and defines a mechanism by which ion homeostasis integrates biomechanical and biochemical signaling to promote medulloblastoma aggression.

Abstract 1882: Passenger gene co-amplification leads to collateral vulnerabilities in cancer

Abstract The activation of oncogenes via genomic amplification is a hallmark of the cancer genomes, yet such amplifications frequently also encompass neighboring genes. Such passenger genes are involved in essential cellular activities. We hypothesized that co-amplification of passenger genes create cancer-specific collateral therapeutic vulnerabilities. To test this, we analyzed one of the most commonly amplified gene locus near MYCN, which is amplified in nearly 25% of neuroblastoma and around 5% of all cancers. We observed that DDX1, a DEAD-Box helicase, is the most frequently co-amplified passenger gene in MYCN-amplified cancers. Using CRISPR/Cas9 loss-of-function screen results from the Cancer Dependency Map across 739 human cancer cell lines, we reveal that cells with DDX1 co-amplification are highly dependent on the mTOR complex 1(mTORC1). Mechanistically, western blot and immunoprecipitation analyses shows that DDX1 expression leads to higher mTORC1 pathway activity through the interaction between DDX1 and alpha-ketoglutarate dehydrogenase(alpha-KGDH) in mitochondria. DDX1 hijacks alpha-KGDH complex, thereby impairing the function of the Krebs cycle by interfering with the conversion of alpha-ketoglutarate to succinyl-coA. Live cell metabolomics shows accumulated alpha-ketoglutarate in turn activates mTORC1 pathway to promote the ATP production via oxidative phosphorylation(OXPHOS) to maintain cell survival. Consequently, interference with mTORC1 function reduced ATP production and led to accumulated alpha-KG leading to cell death, specifically in DDX1 expressing cells. This suggests that co-amplification of a passenger gene can result in collateral vulnerabilities in cancers, which has the potential to transform future therapeutic target discovery in oncology. Citation Format: Yi Bei, Marieluise Kirchner, Luca Brame, Raphaela Fritsche-Guenther, Julia Koeppke, Anja Heeren-Hagemann, Philipp Mertins, Jan Dörr, Anton George Henssen. Passenger gene co-amplification leads to collateral vulnerabilities in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1882.

Abstract 2277: Evaluation of mutation profile of oncogenic signalling pathway in breast cancer among Indian population

Abstract Introduction: Genomic profile of breast cancer is diverse in nature and complex due to heterogeneity among racial groups. In India, it is the leading cause of cancer death and accounts for 13.5% of the total incidence of new cancer cases with a mortality rate of 10.6% irrespective of age and sex in 2020. The growing incidence marks the importance of profiling driver genes that are usually involved in proliferation, cell survival, oxidative stress response, progenitor phenotype, cell growth, apoptosis, and cell cycle regulation. In order to evaluate the mutation profile within breast tumor, we carried out Whole Exome Sequencing (WES) followed by gene analysis which is implicated in oncogenic pathways. Experimental procedures: 40 primary breast cancer patients were recruited from the clinical follow-up at AIIMS, New Delhi, India. With informed consent, tumor and blood were collected after surgery followed by genomic DNA extraction. Library preparation was done by adopting a protocol developed by Illumina. Exonic regions were captured by using Trueseq Exome kit which covers ≥ 80% of whole-exome and sequencing was performed by utilizing Illumina platform as per the manufacturer’s instruction. Bioinformatics analyses were carried out through an in-house developed pipeline. We identified altered genes by comparing them with the matched control and further filtered them on the basis of their functional impact. Results: In our study, a recurrent mutation in RTK-RAS, Notch, PI3K, WNT, Hippo, Myc, cell cycle, p53, TGF-β, NRF2 pathways were reported among 40 individuals. We found a total of 263 altered genes, out of these 186 genes were driver genes comprise 88 tumor suppressor genes and 98 oncogenes while the rest are passenger genes. In terms of SNP Class- >58%- missense, <4%-silent, <38%-nonsense mutations. These SNPs have their phenotypic impact such as high, moderate, modifier, and low which accounts <2.4%, 8-12%, >75%, and <10% respectively. Missense mutation has a greater fraction of C>T transitions followed by C>A transversion. Moreover, we also identified p53, PIK3CA, EIF4EBP1 and ALK as a top mutated genes. A hotspot mutation H1047R in PIK3CA and R56W, as well as R99S in EIF4EBP1, were account for subsequently 20%, 25%, and 15% samples along with hotspot region in MAML3. Conclusions: Here we demonstrate exclusive molecular profiling of the oncogenic pathways of breast cancer in the Indian population. Apart from nonsynonymous substitution, we also revealed recurrent mutation within a specific position or region of gene involved in the RTK-RAS, Notch, and PIK3CA network. Overall this study will improve insight for commonly mutated genes with a primary objective of screening, diagnosis, prognosis along risk stratification. In addition, this could be used to identify specific targetable candidate mutation gene panels with an overall objective of personalized drug therapy. Citation Format: Rahul Kumar, Anurag Srivastava, Usha Agrawal, S.V.S. Deo, Sandeep R. Mathur, Ajay Gogia, Pranay Tanwar. Evaluation of mutation profile of oncogenic signalling pathway in breast cancer among Indian population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2277.

Conceptual Evolution and Current Approach to Spitz Tumors.

Over the past several decades, the study of Spitz neoplasms has flourished, with expanded conceptualization and refined terminology, providing a framework for the assessment and classification of Spitz nevi, atypical Spitz Tumors, and Spitz melanoma. Cancer genomics have generated concepts such as driver and passenger genes and clonal evolution, which can be applied to Spitz tumors. Herein, we provide a historical perspective, followed by a summary of current knowledge and clinical approaches for these challenging tumors.

Complexity against current cancer research: Are we on the wrong track?

Cancer genetics has led to major discoveries, including protooncogene and tumor-suppressor concepts, and cancer genomics generated concepts like driver and passenger genes, revealed tumor heterogeneity and clonal evolution. Reconstructing trajectories of tumorigenesis using spatial and single-cell genomics is possible. Patient stratification and prognostic parameters have been improved. Yet, despite these advances, successful translation into targeted therapies has been scarce and mostly limited to kinase inhibitors. Here, we argue that current cancer research may be on the wrong track, by considering cancer more as a "monogenic" disease, trying to extract common information from thousands of patients, while not properly considering complexity and individual diversity. We suggest to empower a systems cancer approach which reconstructs the information network that has been altered by the tumorigenic events, to analyze hierarchies and predict (druggable) key nodes that could interfere with/block the aberrant information transfer. We also argue that the interindividual variability between patients of similar cohorts is too high to extract common polygenic network information from large numbers of patients and argue in favor of an individualized approach. The analysis we propose would require a structured multinational and multidisciplinary effort, in which clinicians, and cancer, developmental, cell and computational biologists together with mathematicians and informaticians develop dynamic regulatory networks which integrate the entire information transfer in and between cells and organs in (patho)physiological conditions, revealing hierarchies and available drugs to interfere with key regulators. Based on this blueprint, the altered information transfer in individual cancers could be modeled and possible targeted (combo)therapies proposed.

CRISPR/Cas9-mediated SARM1 knockout and epitope-tagged mice reveal that SARM1 does not regulate nuclear transcription, but is expressed in macrophages

SARM1 is a toll/interleukin-1 receptor -domain containing protein, with roles proposed in both innate immunity and neuronal degeneration. Murine SARM1 has been reported to regulate the transcription of chemokines in both neurons andmacrophages; however, the extent to which SARM1 contributesto transcription regulation remains to be fully understood. Here, we identify differential gene expression in bone-marrow-derived macrophages (BMDMs) from C57BL/6 congenic 129 ES cell-derived Sarm1-/- mice compared with wild type (WT). However, we found that passenger genes, which are derived from the 129 donor strain of mice that flank the Sarm1 locus, confound interpretation of the results, since many of the identified differentially regulated genes come from this region. To re-examine the transcriptional role of SARM1 in the absence of passenger genes, here we generated three Sarm1-/- mice using CRISPR/Cas9. Treatment of neurons from these mice with vincristine, a chemotherapeutic drug causing axonal degeneration, confirmed SARM1's function in that process; however, these mice also showed that lack of SARM1 has no impact on transcription of genes previously shown to be affected such as chemokines. To gain further insight into SARM1 function, we generated an epitope-tagged SARM1 mouse. In these mice, we observed high SARM1 protein expression in the brain and brainstem and lower but detectable levels in macrophages. Overall, the generation of these SARM1 knockout and epitope-tagged mice has clarified that SARM1 is expressed in mouse macrophages yet has no general role in macrophage transcriptional regulation and has provided important new models to further explore SARM1 function.

Assessment of Mosaicism and Detection of Cryptic Alleles in CRISPR/Cas9-Engineered Neurofibromatosis Type 1 and TP53 Mutant Porcine Models Reveals Overlooked Challenges in Precision Modeling of Human Diseases.

Genome editing in pigs has been made efficient, practical, and economically viable by the CRISPR/Cas9 platform, representing a promising new era in translational modeling of human disease for research and preclinical development of therapies and devices. Porcine embryo microinjection provides a universally available, efficient option over somatic-cell nuclear transfer, but requires that critical considerations be made in genotypic validation of the models that routinely go unaddressed. Accurate validation of genotypes is especially important when modeling genetic disorders, such as neurofibromatosis type 1 (NF1) that exhibits complex genotype–phenotypic relationships. NF1, an autosomal dominant disorder, is particularly hard to model as it manifests very differently across patients, and even within families, with over 3,000 disease-associated mutations of the neurofibromin 1 (NF1) gene identified. The precise nature of the mutations plays a role in the complex phenotypic presentation of the disorder that includes benign and malignant peripheral and central nervous system tumors, a variety of motor deficits and debilitating cognitive impairments and musculoskeletal, cardiovascular, and gastrointestinal disorders. NF1 can also often involve mutations in passenger genes such as TP53. In this manuscript, we describe the creation of three novel porcine models of NF1 and a model additionally harboring a mutation in TP53 by embryo microinjection of CRISPR/Cas9. We present the challenges encountered in validation of genotypes and the methodological strategies developed to counter the hurdles. We present simple options for quantifying level of mosaicism: a quantitative method (targeted amplicon sequencing) for small edits such as SNPs and indels and a semiquantitative method (competitive PCR) for large edits. Characterization of mosaicism allowed for strategic selection of founder pigs for rapid, economical expansion of genetically defined lines. We also present commonly observed unexpected DNA repair products (i.e., structural variants or cryptic alleles) that are refractory to PCR amplification and thus evade detection. We present the use of copy number variance assays to overcome hurdles in detecting cryptic alleles. The report provides a framework for genotypic validation of porcine models created by embryo microinjection and the expansion of lines in an efficient manner.