Loss of USP28 and SPINT2 expression promotes cancer cell survival after whole genome doubling

Background Whole genome doubling is a frequent event during cancer evolution and shapes the cancer genome due to the occurrence of chromosomal instability. Yet, erroneously arising human tetraploid cells usually do not proliferate due to p53 activation that leads to CDKN1A expression, cell cycle arrest, senescence and/or apoptosis. Methods To uncover the barriers that block the proliferation of tetraploids, we performed a RNAi mediated genome-wide screen in a human colorectal cancer cell line (HCT116). Results We identified 140 genes whose depletion improved the survival of tetraploid cells and characterized in depth two of them: SPINT2 and USP28. We found that SPINT2 is a general regulator of CDKN1A transcription via histone acetylation. Using mass spectrometry and immunoprecipitation, we found that USP28 interacts with NuMA1 and affects centrosome clustering. Tetraploid cells accumulate DNA damage and loss of USP28 reduces checkpoint activation, thus facilitating their proliferation. Conclusions Our results indicate three aspects that contribute to the survival of tetraploid cells: (i) increased mitogenic signaling and reduced expression of cell cycle inhibitors, (ii) the ability to establish functional bipolar spindles and (iii) reduced DNA damage signaling.

Novel Tumor-Specific Antigens for Immunotherapy Identified From Multi-omics Profiling in Thymic Carcinomas

Thymic carcinoma (TC) is the most aggressive thymic epithelial neoplasm. TC patients with microsatellite instability, whole-genome doubling, or alternative tumor-specific antigens from gene fusion are most likely to benefit from immunotherapies. However, due to the rarity of this disease, how to prioritize the putative biomarkers and what constitutes an optimal treatment regimen remains largely unknown. Therefore, we integrated genomic and transcriptomic analyses from TC patients and revealed that frameshift indels in KMT2C and CYLD frequently produce neoantigens. Moreover, a median of 3 fusion-derived neoantigens was predicted across affected patients, especially the CATSPERB-TC2N neoantigens that were recurrently predicted in TC patients. Lastly, potentially actionable alterations with early levels of evidence were uncovered and could be used for designing clinical trials. In summary, this study shed light on our understanding of tumorigenesis and presented new avenues for molecular characterization and immunotherapy in TC.

A Genetic Model for Central Chondrosarcoma Evolution Correlates with Patient Outcome

The treatment options for central chondrosarcoma are limited, and prognoses are generally unreliable. The presence and absence of mutations in IDH1, and IDH2 are defining events, and TERT mutations have been recently been associated with poor outcome. Despite this, molecular biomarkers are lacking. Here, analysing data from 356 patients, comprising results from whole genome sequencing (n=68), digital droplet PCR (n=346), and methylation arrays (n=57), we present a comprehensive genetic analysis of chondrosarcoma and suggest its clinical utility. Methylation profiles, TERT promoter mutations, genome doubling with prior haploidisation, and age at diagnosis of high grade, distinguish IDH1-mutant, IDH2-mutant and IDH wildtype tumours. The majority of IDH2-mutant tumours harbour TERT mutations, though a significant reduction in survival is only found in the less common mutational combination of IDH1 and TERT. We suggest that diagnostic testing for IDH1, IDH2 and TERT mutations could guide clinical monitoring and prognostication.

Two Is Company, but Four Is a Party—Challenges of Tetraploidization for Cell Wall Dynamics and Efficient Tip-Growth in Pollen

Some cells grow by an intricately coordinated process called tip-growth, which allows the formation of long tubular structures by a remarkable increase in cell surface-to-volume ratio and cell expansion across vast distances. On a broad evolutionary scale, tip-growth has been extraordinarily successful, as indicated by its recurrent ‘re-discovery’ throughout evolutionary time in all major land plant taxa which allowed for the functional diversification of tip-growing cell types across gametophytic and sporophytic life-phases. All major land plant lineages have experienced (recurrent) polyploidization events and subsequent re-diploidization that may have positively contributed to plant adaptive evolutionary processes. How individual cells respond to genome-doubling on a shorter evolutionary scale has not been addressed as elaborately. Nevertheless, it is clear that when polyploids first form, they face numerous important challenges that must be overcome for lineages to persist. Evidence in the literature suggests that tip-growth is one of those processes. Here, I discuss the literature to present hypotheses about how polyploidization events may challenge efficient tip-growth and strategies which may overcome them: I first review the complex and multi-layered processes by which tip-growing cells maintain their cell wall integrity and steady growth. I will then discuss how they may be affected by the cellular changes that accompany genome-doubling. Finally, I will depict possible mechanisms polyploid plants may evolve to compensate for the effects caused by genome-doubling to regain diploid-like growth, particularly focusing on cell wall dynamics and the subcellular machinery they are controlled by.

830 Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes reveals immune-excluded phenotype related to APOBEC signature and clonal evolution of cancer

BackgroundLittle is known about bridging clonal heterogeneity into the resistance of immune checkpoint inhibitors (ICI). Recent reports showed that excluded tumor-infiltrating lymphocytes (TIL) into stroma assessed by an artificial intelligence (AI)-powered spatial TIL analyzer, Lunit SCOPE IO, was related to loss-of-heterozygosity of HLA genes which would be one of crucial resistance pathways of ICI.1 In the current study, we hypothesized that Immune-excluded phenotype called by Lunit SCOPE IO would be related to clonal heterogeneity resulted from genome-wide accidents during early carcinogenesis which may cause an improper targeting of TIL for diverse clones with multiple genomic aberrations.MethodsFor spatial TIL analysis, we applied Lunit SCOPE IO1 which automatically detects TIL and segmentizes cancer area and stroma, then it classified Immune phenotype of 1 mm2-sized grid in H&E image. Inflamed score or Immune-excluded score were defined as the proportion of Inflamed phenotype, which is high intra-tumoral TIL density, or Immune-excluded phenotype, which is exclusively high TIL density only in stroma, within a whole-slide image, respectively. We evaluated the correlation of Immune phenotype with APOBEC mutational signature by single-base substitution (SBS) signature 2 and/or SBS13,2 whole-genome doubling, and subclonal genome fraction which reflects intra-tumoral heterogeneity,3 and clusters of T cell receptor (TCR) repertoire 4 derived from previous reports of The Cancer Genome Atlas (TCGA), consists of 7,467 tumor samples from 22 cancer types.Abstract 830 Table 1Correlation between immune phenotype and clonal evolution of cancer [* Median (95% confidence interval)]ResultsIn the TCGA pan-carcinoma database, APOBEC mutational signature was significantly correlated with increased ratio of cancer stroma to cancer epithelium (median 0.866 vs 1.19, fold change +37.4%), and increased TIL density in cancer stroma (median 558 vs 764 / mm2, fold change +36.9%), but it was not correlated with intra-tumoral TIL density (median 63 vs 59 / mm2, fold change -6.3%). Interestingly, Immune-excluded score (IES) called by Lunit SCOPE IO was positively correlated with APOBEC mutational signature as well as expression levels of APOBEC1, APOBEC3A, and APOBEC3B, whole-genome doubling, and subclonal genome fraction, respectively, while Inflamed score (IS) or immune cytolytic activity (GZMA and PRF1 expressions) was negatively or not significantly correlated to those variables (table 1). TCR repertoire was expanded in the tumor samples with high IS (spearman rho = 0.279), but it was not increased in those with high IES (spearman rho = -0.0595).ConclusionsThere is a significant correlation between distinct TIL deposition in stroma, or Immune-excluded phenotype, with APOBEC-attributed clonal expansion of cancer, without proper expansion of TCR repertoire.ReferencesOck CY, Park C, Paeng K, Yoo D, Kim S, Park S, Lee SH, Mok T, Bang YJ. Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes reveals distinct genomic profile of immune excluded phenotype in pan-carcinoma. Cancer Res 2021;81(Supp 13):1908.Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, Tian Ng AW, Wu Y, Boot A, Covington KR, Gordenin DA, Bergstrom EN, Islam SMA, Lopez-Bigas N, Klimczak LJ, McPherson JR, Morganella S, Sabarinathan R, Wheeler DA, Mustonen V, PCAWG Mutational Signatures Working Group, Getz G, Rozen SG, Stratton MR, PCAWG Consortium. The repertoire of mutational signatures in human cancer. Nature 2020;578(7793):94–101.Taylor AM, Shih J, Ha G, Gao GF, Zhang X, Berger AC, Schumacher SE, Wang C, Hu H, Liu J, Lazar AJ, Cancer Genome Atlas Research Network, Cherniack AD, Beroukhim R, Meyerson M. Genomic and functional approaches to understanding cancer aneuploidy. Cancer Cell 2018;33(4):676–689.e3.Zhang H, Liu L, Zhang J, Chen J, Ye J, Shukla S, Qiao J, Zhan X, Chen H, Wu CJ, Fu YX, Li B. Investigation of antigen-specific T-Cell receptor clusters in human cancers. Clin Cancer Res 2020;26(6):1359–1371.

Clinical sequencing of soft tissue and bone sarcomas delineates diverse genomic landscapes and potential therapeutic targets

The genetic, biologic, and clinical heterogeneity of sarcomas poses a challenge for the identification of therapeutic targets, clinical research, and advancing patient care. Because there are > 100 sarcoma subtypes, in-depth genetic studies have focused on one or a few subtypes. Herein, we report a comparative genetic analyses analysis of 2,138 sarcomas representing 45 pathological entities. This cohort was prospectively analyzed using targeted sequencing to characterize subtype-specific somatic alterations in targetable pathways, rates of whole genome doubling, mutational signatures, and subtype-agnostic genomic clusters. The most common alterations were in cell cycle control and TP53, receptor tyrosine kinases/PI3K/RAS, and epigenetic regulators. Subtype-specific associations included TERT amplification in intimal sarcoma and SWI/SNF alterations in uterine adenosarcoma. Tumor mutational burden, while low compared to other cancers, varied between and within subtypes. This resource will improve sarcoma models, motivate studies of subtype-specific alterations, and inform investigations of genetic factors and their correlations with treatment response.

Distinct and common features of numerical and structural chromosomal instability across different cancer types

A large proportion of tumours is characterised by numerical or structural chromosomal instability (CIN), defined as an increased rate of gaining or losing whole chromosomes (W-CIN) or of accumulating structural aberrations (S-CIN). Both W-CIN and S-CIN are associated with tumourigenesis, cancer progression, treatment resistance and clinical outcome. Although S-CIN and W-CIN can co-occur, they are initiated by different molecular events. By analysing tumour genomic data from 32 cancer types, we show that the majority of tumours with high levels of W-CIN underwent whole genome doubling, whereas S-CIN levels are strongly associated to homologous recombination deficiency. Both CIN phenotypes are prognostic in several cancer types. Most drugs are less efficient in high CIN cell lines, but we report also compounds and drugs which could specifically target S-CIN or W-CIN. By analysing associations of gene expression with CIN at the pathway and single gene level, we complement gene signatures for CIN and report that the drug resistance gene CKS1B is strongly associated to both S-CIN and W-CIN. Finally, we identify a potential copy number dependent mechanism for the activation of the PI3K pathway in high CIN tumours.