Clonal and "Intrinsic" Heterogeneity of Somatic Variants in Microsatellite-Stable Colorectal Carcinomas and Their Metastases.

To test the traditional model of tumor progression, Darwinian-type evolution, against the more recent Big Bang model, we selected 6 microsatellite-stable colorectal standard-type adenocarcinomas and their synchronous lymph node and liver metastases. Somatic genomic variants were identified by whole-exome sequencing (WES) of large tumor fragments from the primaries and 1 liver metastasis each, and used to design targeted resequencing next-generation sequencing (NGS) panels, 1 per case. Targeted deep resequencing (mean coverage, 2725; median, 2222) was performed with DNA from punch samples (1-mm tissue microarrayer needles) obtained from different regions of the primaries and their metastases. In total, 255 genomic variants were interrogated in 108 punch samples. Clonal heterogeneity was infrequent: a pattern of clonal heterogeneity consistent with a role in metastasis formation was observed only in 1 case in a single gene (p. Asp604Tyr of the PTPRT gene). However, when comparing variant allele frequencies (VAFs) of genomic variants in adjacent positions on chromosomes ("matched genomic variant loci") across punch samples, differences that exceeded 2 SD of the NGS assay variations (ad hoc dubbed VAF dysbalance) were observed in 7.1% of the punch samples (2.6%-12.0% per case), which indicates an intricate intermixing of mutated and nonmutated tumor cells ("intrinsic heterogeneity"). Additional OncoScan array analyses on a subset of the punch samples (31 in total) showed gross genomic aberrations as a possible explanation in only some (39.2%) of the matched genomic variant loci with VAF dysbalance. Our study provides a fairly direct (statistical model-free) view of the genomic states of microsatellite-stable colorectal carcinomas and their metastases, and suggests that Darwinian-type tumor evolution is not the key pathway of the metastasizing disease; instead, we recorded an "intrinsic" genomic heterogeneity, which may echo an initial Big Bang-like event.

Three-dimensional genome landscape comprehensively reveals patterns of spatial gene regulation in papillary and anaplastic thyroid cancers: a study using representative cell lines for each cancer type.

BACKGROUND: Spatial chromatin structure is intricately linked with somatic aberrations, and somatic mutations of various cancer-related genes, termed co-mutations (CoMuts), occur in certain patterns during cancer initiation and progression. The functional mechanisms underlying these genetic events remain largely unclear in thyroid cancer (TC). With discrepant differentiation, papillary thyroid cancer (PTC) and anaplastic thyroid cancer (ATC) differ greatly in characteristics and prognosis. We aimed to reveal the spatial gene alterations and regulations between the two TC subtypes. METHODS: We systematically investigated and compared the spatial co-mutations between ATC (8305C), PTC (BCPAP and TPC-1), and normal thyroid cells (Nthy-ori-3-1). We constructed a framework integrating whole-genome sequencing (WGS), high-throughput chromosome conformation capture (Hi-C), and transcriptome sequencing, to systematically detect the associations between the somatic co-mutations of cancer-related genes, structural variations (SVs), copy number variations (CNVs), and high-order chromatin conformation. RESULTS: Spatial co-mutation hotspots were enriched around topologically associating domains (TADs) in TC. A common set of 227 boundaries were identified in both ATC and PTC, with significant overlaps between them. The spatial proximities of the co-mutated gene pairs in the two TC types were significantly greater than in the gene-level and overall backgrounds, and ATC cells had higher TAD contact frequency with CoMuts > 10 compared with PTC cells. Compared with normal thyroid cells, in ATC the number of the created novel three-dimensional chromatin structural domains increased by 10%, and the number of shifted TADs decreased by 7%. We found five TAD blocks with CoMut genes/events specific to ATC with certain mutations in genes including MAST-NSUN4, AM129B/TRUB2, COL5A1/PPP1R26, PPP1R26/GPSM1/CCDC183, and PRAC2/DLX4. For the majority of ATC and PTC cells, the HOXA10 and HIF2α signals close to the transcription start sites of CoMut genes within TADs were significantly stronger than those at the background. CNV breakpoints significantly overlapped with TAD boundaries in both TC subtypes. ATCs had more CNV losses overlapping with TAD boundaries, and noncoding SVs involved in intrachromosomal SVs, amplified inversions, and tandem duplication differed between ATC and PTC. TADs with short range were more abundant in ATC than PTC. More switches of A/B compartment types existed in ATC cells compared with PTC. Gene expression was significantly synchronized, and orchestrated by complex epigenetics and regulatory elements. CONCLUSION: Chromatin interactions and gene alterations and regulations are largely heterogeneous in TC. CNVs and complex SVs may function in the TC genome by interplaying with TADs, and are largely different between ATC and PTC. Complexity of TC genomes, which are highly organized by 3D genome-wide interactions mediating mutational and structural variations and gene activation, may have been largely underappreciated. Our comprehensive analysis may provide key evidence and targets for more customized diagnosis and treatment of TC.

Comparative analysis of capture methods for genomic profiling of circulating tumor cells in colorectal cancer.

The genomic profiling of circulating tumor cells (CTCs) in the bloodstream should provide clinically relevant information on therapeutic efficacy and help predict cancer survival. Here, we contrasted the genomic profiles of CTC pools recovered from metastatic colorectal cancer (mCRC) patients using different enrichment strategies (CellSearch, Parsortix, and FACS). Mutations inferred in the CTC pools differed depending on the enrichment strategy and, in all cases, represented a subset of the mutations detected in the matched primary tumor samples. However, the CTC pools from Parsortix, and in part, CellSearch, showed diversity estimates, mutational signatures, and drug-suitability scores remarkably close to those found in matching primary tumor samples. In addition, FACS CTC pools were enriched in apparent sequencing artifacts, leading to much higher genomic diversity estimates. Our results highlight the utility of CTCs to assess the genomic heterogeneity of individual tumors and help clinicians prioritize drugs in mCRC.

Genomic heterogeneity and copy number variant burden are associated with poor recurrence-free survival and 11q loss in human papillomavirus-positive squamous cell carcinoma of the oropharynx.

BACKGROUND: Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States. Favorable treatment outcomes have led to increased interest in treatment de-escalation to reduce treatment morbidity as well as the development of prognostic markers to identify appropriately low-risk patients. Intratumoral genomic heterogeneity and copy number alteration burden have been demonstrated to be predictive of poor outcomes in many other cancers; therefore, we sought to determine whether intratumor heterogeneity and genomic instability are associated with poor outcomes in HPV+ OPSCC. METHODS: Tumor heterogeneity estimates were made based on targeted exome sequencing of 45 patients with HPV+ OPSCC tumors. Analysis of an additional cohort of HPV+ OPSCC tumors lacking matched normal sequencing allowed copy number analysis of 99 patient tumors. RESULTS: High intratumorally genomic heterogeneity and high numbers of copy number alterations were strongly associated with worse recurrence-free survival. Tumors with higher heterogeneity and frequent copy number alterations were associated with loss of distal 11q, which encodes key genes related to double-strand break repair, including ATM and MRE11A. CONCLUSIONS: Both intratumor genomic heterogeneity and high-burden copy number alterations are strongly associated with poor recurrence-free survival in patients with HPV+ OPSCC. The drivers of genomic instability and heterogeneity in these tumors remains to be elucidated. However, 11q loss and defective DNA double-strand break repair have been associated with genomic instability in other solid tumors. Copy number alteration burden and intratumoral heterogeneity represent promising avenues for risk stratification of patients with HPV+OPSCC.

Adaptive and nonadaptive causes of heterogeneity in genetic differentiation across the Mimulus guttatus genome.

Genetic diversity becomes structured among populations over time due to genetic drift and divergent selection. Although population structure is often treated as a uniform underlying factor, recent resequencing studies of wild populations have demonstrated that diversity in many regions of the genome may be structured quite dissimilar to the genome-wide pattern. Here, we explored the adaptive and nonadaptive causes of such genomic heterogeneity using population-level, whole genome resequencing data obtained from annual Mimulus guttatus individuals collected across a rugged environment landscape. We found substantial variation in how genetic differentiation is structured both within and between chromosomes, although, in contrast to other studies, known inversion polymorphisms appear to serve only minor roles in this heterogeneity. In addition, much of the genome can be clustered into eight among-population genetic differentiation patterns, but only two of these clusters are particularly consistent with patterns of isolation by distance. By performing genotype-environment association analysis, we also identified genomic intervals where local adaptation to specific climate factors has accentuated genetic differentiation among populations, and candidate genes in these windows indicate climate adaptation may proceed through changes affecting specialized metabolism, drought resistance, and development. Finally, by integrating our findings with previous studies, we show that multiple aspects of plant reproductive biology may be common targets of balancing selection and that variants historically involved in climate adaptation among populations have probably also fuelled rapid adaptation to microgeographic environmental variation within sites.

Inter-tumor genomic heterogeneity of breast cancers: comprehensive genomic profile of primary early breast cancers and relapses.

BACKGROUND: The breast cancer genome dynamically evolves during malignant progression and recurrence. We investigated the genomic profiles of primary early-stage breast cancers and matched relapses to elucidate the molecular underpinnings of the metastatic process, focusing on potentially actionable alterations in the recurrences. METHODS: A mono-institutional cohort of 128 patients with breast cancers (n = 68 luminal B HER2, n = 6 luminal B HER2+, n = 1 HER2+ non-luminal, n = 56 triple negative) and at least one recurrence in a timeframe of 17 years was evaluated. Next-generation sequencing comprehensive genomic profiling was performed on 289 formalin-fixed paraffin-embedded (FFPE) samples, including primary tumors and matched relapses. Correlations of genomic aberrations with clinicopathologic factors and time to breast cancer relapse were analyzed. RESULTS: Genomic data were available for 188 of 289 FFPE samples that achieved the sequencing quality parameters (failure rate 34.9%), including 106 primary tumors and 82 relapses. All primary and relapse samples harbored at least one genomic alteration, with a median number of six alterations per sample (range 1-16). The most frequent somatic genomic alterations were mutations of TP53 (primary tumors = 49%, relapses = 49%) and PIK3CA (primary tumors = 33%, relapses = 30%). Distinctive genomic alterations of primary tumors were significantly associated with molecular subtypes. TP53, PIK3R1, and NF1 somatic alterations were more frequently detected in triple negative tumors (p value < 0.05); CCND1, FGF3, and FGFR1 copy number gains were recurrently identified in luminal cases (p value < 0.05). Moreover, TP53 mutations and MYC amplification were significantly and independently associated with a shorter time to relapse (p value < 0.05). Molecular subtype changes between primary tumors and relapses were seen in 10 of 128 (7.8%) cases. Most driver genomic alterations (55.8%) were shared between primary tumors and matched recurrences. However, in 39 of 61 cases (63.9%), additional private alterations were detected in the relapse samples only, including 12 patients with potentially actionable aberrations. CONCLUSIONS: Specific genomic aberrations of primary breast cancers were associated with time to relapse. Primary tumors and matched recurrences showed a core of shared driver genomic aberrations but private actionable alterations have been identified in the relapses.

Somatic alterations detected in diagnostic prostate biopsies provide an inadequate representation of multifocal prostate cancer.

BACKGROUND: The majority of clinical prostate cancers are multifocal with morphological and molecular heterogeneity. Adequate tissue representation is crucial for the clinical utility of multigene panel sequencing of core needle biopsies. The aim of this study was to evaluate the genomic heterogeneity in multifocal prostate cancer and to analyze how representative preoperative biopsies are of spatially separated tumor foci. METHODS: We analyzed at least 2 tumor foci and 1 to 3 preoperative biopsy cores from 11 patients. Diagnostic biopsies, as well as fresh frozen and formalin-fixed paraffin-embedded samples, from major tumor foci of radical prostatectomy specimens were macrodissected for the enrichment of tumor tissue. DNA was extracted and sequenced. We analyzed structural alterations, mutations, and copy number variations and compared the genomic profiles of tumor foci with those of preoperative biopsies. RESULTS: Alterations were rarely shared between foci, indicating a high degree of genomic heterogeneity. In 8 of 11 men at least 1 tumor focus was represented by the biopsies defined as harboring at least 1 common clonal somatic event. In only one case, somatic alterations from two spatially separate tumors were identified in the biopsies. Of the mutations and structural variants detected in fresh frozen or formalin-fixed paraffin-embedded prostatectomy material, only an average of 19% (range 0-44) and 55% (range 0-100), respectively, were found in preoperative biopsies where a common somatic origin was established. CONCLUSIONS: Multifocal prostate cancer is a somatically heterogeneous disease in which systematic needle biopsies do not provide sufficient molecular representation of the somatic alterations detected in spatially distinct tumor areas. Targeted biopsies, directed at separate tumor foci, could potentially improve tissue representation of these heterogeneous foci in preoperative biopsies.

Genomic and transcriptional heterogeneity of multifocal hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) often presents with multiple nodules within the liver, with limited effective interventions. The high genetic heterogeneity of HCC might be the major cause of treatment failure. We aimed to characterize genomic heterogeneity, infer clonal evolution, investigate RNA expression pattern and explore tumour immune microenvironment profile of multifocal HCC. PATIENTS AND METHODS: Whole-exome sequencing and RNA sequencing were carried out in 34 tumours and 6 adjacent normal liver tissue samples from 6 multifocal HCC patients. Protein expression of Ki67, AFP, P53, Survivin and CD8 was detected by immunohistochemistry. Fluorescence in situ hybridization was carried out to validate the amplification status of sorafenib-targeted genes. RESULTS: We deciphered genomic and transcriptional heterogeneity among tumours in each multifocal HCC patient including mutational profiles, copy number alterations, tumour evolutionary trajectory and tumour immune microenvironment profiles. Of note, sorafenib-targeted alterations were identified in the trunk of phylogenetic tree in only one out of the six patients, which may explain the relative low treatment response rate to sorafenib in clinical practice. Moreover, we demonstrated RNA expression patterns and tumour immune microenvironment profiles of all nodules. We found that RNA expression pattern was associated with Edmondson-Steiner grading. Based on the differential expression of 66 reported immune markers, unsupervised hierarchical clustering analysis of 34 nodules identified immune subsets: one low expression cluster with seven nodules and one high expression cluster with 11 nodules. CD8+ T cells were more enriched in nodules of the high expression cluster. CONCLUSIONS: Our study provided a detailed view of genomic and transcriptional heterogeneity, clonal evolution and immune infiltration of multifocal HCC. The heterogeneity of druggable targets and immune landscape might help interpret the clinical responsiveness to targeted drugs and immunotherapy for multifocal HCC patients.

Bacterial Genotyping of Central Nervous System Tuberculosis in South Africa: Heterogenic Mycobacterium tuberculosis Infection and Predominance of Lineage 4.

Tuberculous meningitis (TBM), the most severe extrapulmonary manifestation of tuberculosis, is caused by the pathogen Mycobacterium tuberculosis The M. tuberculosis complex includes seven lineages, all described to harbor a unique geographical dissemination pattern and clinical presentation. In this study, we set out to determine whether a certain M. tuberculosis lineage demonstrated tropism to cause TBM in patients from Cape Town, South Africa. DNA was extracted from formalin-fixed paraffin-embedded central nervous system (CNS) tissue from a unique neuropathological cohort of 83 TBM patients, collected between 1975 and 2012. M. tuberculosis lineages 1, 2, 3, and 4 were determined using an allele-specific PCR and Sanger sequencing. Of the 83 patient specimens tested, bacterial characterization could be performed on 46 specimens (55%). M. tuberculosis lineage 4 was present in 26 patient specimens (56%), and non-lineage 4 was identified in 10 cases (22%). Moreover, genomic heterogeneity was detected in the CNS specimens of 7 adults and 3 children. We could show that infection of the CNS is not restricted to a single M. tuberculosis lineage and that even young children with rapid progression of disease can harbor more than one M. tuberculosis lineage in the CNS.

Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve lung adenocarcinoma.

BACKGROUND: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. METHODS: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. RESULTS: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). CONCLUSIONS: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.

Pathogenic BRCA1 mutations may be necessary but not sufficient for tissue genomic heterogeneity: Deep sequencing data from ovarian cancer patients.

BACKGROUND: Tissue genomic heterogeneity (t-HET) in patients with epithelial ovarian cancer (OVCA) is related to tissue plasticity, i.e., flexibility to adapt to adverse molecular environments. Here, we interrogated the presence and clinical relevance of OVCA t-HET. METHODS: We applied high-depth (>2000×) sequencing on 297 paraffin tissue samples (fallopian tubes, ovaries, intra-abdominal metastases) from 71 treatment-naïve patients who subsequently received first-line platinum-based chemotherapy. Based on tissue mutation patterns, we distinguished tissue genotypes into: no mutation (33/297 samples; 11.1%), stable (173; 58.2%) and unstable (91; 30.7%). We profiled genotypes per patient and assessed t-HET in 69 patients. Predicted pathogenic mutations refer to germline and/or tissues. RESULTS: Among all 71 patients, 46 (64.8%) had pathogenic BRCA1 mutations and 15 (21.7%) had BRCA1/2 disruption (i.e., pathogenic mutations with position-LOH). We classified 29 patients with t-HET (42%), all with pathogenic BRCA1; t-HET was observed in 64% with such mutations (p < 0.001). As opposed to non-t-HET, matched tissues in t-HET shared pathogenic BRCA1 (p < 0.001) but not BRCA2 and TP53. Germline BRCA1 mutations in tissues exhibited position-LOH; heterozygous status; or, partial loss of the inherited allele accompanied by additional clonal mutations. Patients with t-HET had worse outcome (log-rank p = 0.048 [progression-free]; p = 0.037 [overall survival]), including 12/15 patients with disrupted BRCA1/2 and 3 BRCA1 carriers with partial germline loss in tissues. CONCLUSIONS: Pathogenic BRCA1 mutations appear necessary but may not be sufficient for the establishment of t-HET. t-HET may be associated with worse outcome, including in patients with disrupted BRCA1/2, which is usually considered as a favourable marker. OVCA t-HET may need to be addressed for treatment decisions.

Liquid Biopsies for Monitoring Temporal Genomic Heterogeneity in Breast and Colon Cancers.

Cancer is a spatial and temporal dynamic disease where differently evolving genetic clones are responsible for progression. In this landscape, the genomic heterogeneity of the primary tumours can be captured by deep-sequencing representative spatial samples. However, the recognition of genetic alterations responsible for tumour evolution remains a challenging task. Recently, the "liquid biopsy" was recognized as a powerful real-time approach for the molecular monitoring of this dynamic disease. The term "liquid biopsy" generally refers to the use of circulating (cell-free) tumour DNA (ctDNA) and circulating tumour cells (CTCs) as non-invasive biomarkers for the early diagnosis, prognosis, monitoring of clinical progression, and response to treatment in different types of tumours, including the highly genomic heterogeneous breast cancer. The implementation and standardization of both approaches are still needed to achieve the required sensitivity and specificity to successfully analyze heterogenous tumours, but pivotal studies, in particular those concerning colorectal cancer, have shown the feasibility and usefulness of liquid biopsy for monitoring the Darwinian clonal evolution from an early to a metastatic stage.

Uncovering the genomic heterogeneity of multifocal breast cancer.

Multifocal breast cancer (MFBC), defined as multiple synchronous unilateral lesions of invasive breast cancer, is relatively frequent and has been associated with more aggressive features than unifocal cancer. Here, we aimed to investigate the genomic heterogeneity between MFBC lesions sharing similar histopathological parameters. Characterization of different lesions from 36 patients with ductal MFBC involved the identification of non-silent coding mutations in 360 protein-coding genes (171 tumour and 36 matched normal samples). We selected only patients with lesions presenting the same grade, ER, and HER2 status. Mutations were classified as 'oncogenic' in the case of recurrent substitutions reported in COSMIC or truncating mutations affecting tumour suppressor genes. All mutations identified in a given patient were further interrogated in all samples from that patient through deep resequencing using an orthogonal platform. Whole-genome rearrangement screen was further conducted in 8/36 patients. Twenty-four patients (67%) had substitutions/indels shared by all their lesions, of which 11 carried the same mutations in all lesions, and 13 had lesions with both common and private mutations. Three-quarters of those 24 patients shared oncogenic variants. The remaining 12 patients (33%) did not share any substitution/indels, with inter-lesion heterogeneity observed for oncogenic mutation(s) in genes such as PIK3CA, TP53, GATA3, and PTEN. Genomically heterogeneous lesions tended to be further apart in the mammary gland than homogeneous lesions. Genome-wide analyses of a limited number of patients identified a common somatic background in all studied MFBCs, including those with no mutation in common between the lesions. To conclude, as the number of molecular targeted therapies increases and trials driven by genomic screening are ongoing, our findings highlight the presence of genomic inter-lesion heterogeneity in one-third, despite similar pathological features. This implies that deeper molecular characterization of all MFBC lesions is warranted for the adequate management of those cancers.

Pan-cancer analysis of heterogeneity of tumor mutational burden and genomic mutation under treatment pressure.

BACKGROUND: High tumor mutational burden (TMB) is one of the widely researched predictive biomarkers of immune checkpoint inhibitors and has been shown to be closely related with response to immunotherapy in multiple cancer types. However, for patients who have failed conventional therapy and are about to undergo immunotherapy, there is no consensus recommendation on the timing of tumor sampling for TMB analysis, and the effects of different therapies on TMB have not been clarified. This retrospective observational study aimed to investigate the heterogeneity of TMB and genomic mutation under the treatment pressure. PATIENTS AND METHODS: We retrospectively collected the available genomic and therapeutic information from 8051 samples across 15 tumor types (>50 samples/tumor) found in 30 published studies and investigated the distribution and heterogeneity of TMB under treatment across diverse cohorts. RESULTS: This integrated analysis has shown anticancer treatments increased TMB. Significant effects of treatment on TMB were more frequently observed in tumor types with lower treatment-naïve TMB, including breast, prostate, and pediatric cancers. For different cancer therapies, chemotherapy was prone to be correlated with an increased TMB in most cancer types. Meanwhile, the fraction of the TMB-high category of breast, prostate, and bladder cancers and glioma increased significantly after chemotherapy. Several actionable genes including ERS1 and NF1 in breast cancer, as well as some prognostic markers including TERT in bladder cancer and IDH1 in glioma, were significantly changed in post-chemotherapy tumors compared to treatment-naïve tumors. CONCLUSION: Our study reveals the heterogeneity of TMB under treatment across diverse cancer types and provides evidences that chemotherapy was associated with increases in TMB as well as the fraction of TMB-high category, suggesting that resampling tumor tissues for calculating post-chemotherapy TMB could be a better option for predicting the response to immunotherapy, especially for tumors with initially low TMB.

High degree of genetic differentiation in marine three-spined sticklebacks (Gasterosteus aculeatus).

Populations of widespread marine organisms are typically characterized by a low degree of genetic differentiation in neutral genetic markers, but much less is known about differentiation in genes whose functional roles are associated with specific selection regimes. To uncover possible adaptive population divergence and heterogeneous genomic differentiation in marine three-spined sticklebacks (Gasterosteus aculeatus), we used a candidate gene-based genome-scan approach to analyse variability in 138 microsatellite loci located within/close to (<6 kb) functionally important genes in samples collected from ten geographic locations. The degree of genetic differentiation in markers classified as neutral or under balancing selection-as determined with several outlier detection methods-was low (F(ST) = 0.033 or 0.011, respectively), whereas average FST for directionally selected markers was significantly higher (F(ST) = 0.097). Clustering analyses provided support for genomic and geographic heterogeneity in selection: six genetic clusters were identified based on allele frequency differences in the directionally selected loci, whereas four were identified with the neutral loci. Allelic variation in several loci exhibited significant associations with environmental variables, supporting the conjecture that temperature and salinity, but not optic conditions, are important drivers of adaptive divergence among populations. In general, these results suggest that in spite of the high degree of physical connectivity and gene flow as inferred from neutral marker genes, marine stickleback populations are strongly genetically structured in loci associated with functionally relevant genes.

Integrated clustering signature of genomic heterogeneity, stemness and tumor microenvironment predicts glioma prognosis and immunotherapy response.

BACKGROUND: Glioma is the most frequent primary tumor of the central nervous system. The high heterogeneity of glioma tumors enables them to adapt to challenging environments, leading to resistance to treatment. Therefore, to detect the driving factors and improve the prognosis of glioma, it is essential to have a comprehensive understanding of the genomic heterogeneity, stemness, and immune microenvironment of glioma. METHODS: We classified gliomas into various subtypes based on stemness, genomic heterogeneity, and immune microenvironment consensus clustering analysis. We identified risk hub genes linked to heterogeneous characteristics using WGCNA, LASSO, and multivariate Cox regression analysis and utilized them to create an effective risk model. RESULTS: We thoroughly investigated the genomic heterogeneity, stemness, and immune microenvironment of glioma and identified the risk hub genes RAB42, SH2D4A, and GDF15 based on the TCGA dataset. We developed a risk model utilizing these genes that can reliably predict the prognosis of glioma patients. The risk signature showed a positive correlation with T cell exhaustion and increased infiltration of immunosuppressive cells, and a negative correlation with the response to immunotherapy. Moreover, we discovered that SH2D4A, one of the risk hub genes, could stimulate the migration and proliferation of glioma cells. CONCLUSIONS: This study identified risk hub genes and established a risk model by analyzing the genomic heterogeneity, stemness, and immune microenvironment of glioma. Our findings will facilitate the diagnosis and prediction of glioma prognosis and may lead to potential treatment strategies for glioma.

Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing.

Background: Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflammation-related genes on the clinical prognosis and tumor immunity in PCa remains unclear. Methods: Machine learning methods were utilized to construct and validate a signature using The Cancer Genome Atlas (TCGA) for training, while the Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70769 cohorts for independent validation. The efficacy of the signature in predicting outcomes and its clinical utility were assessed through a series of investigations encompassing in vitro experiments, survival analysis, and nomogram development. The association between the signature and precision medicine was explored via tumor immunity, genomic heterogeneity, therapeutic response, and molecular docking analyses, using bulk and single-cell RNA-sequencing data. Results: We identified 7 inflammation-related genes with prognostic significance and developed an inflammation-related prognostic signature (IRPS) with 6 genes. Furthermore, we demonstrated that both the IRPS and a nomogram integrating risk score and pathologic T stage exhibited excellent predictive ability for the survival outcomes in PCa patients. Moreover, the IRPS was found to be significantly associated with the tumor immune, genomic heterogeneity, therapeutic response, and drug selection. Conclusion: IRPS can serve as a reliable predictor for PCa patients. The signature may provide clinicians with valuable information on the efficacy of therapy and help personalize treatment for PCa patients.

Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer.

Introduction: Macrophages are components of the innate immune system and can play an anti-tumor or pro-tumor role in the tumor microenvironment owing to their high heterogeneity and plasticity. Meanwhile, prostate cancer (PCa) is an immune-sensitive tumor, making it essential to investigate the value of macrophage-associated networks in its prognosis and treatment. Methods: Macrophage-related marker genes (MRMGs) were identified through the comprehensive analysis of single-cell sequencing data from GSE141445 and the impact of macrophages on PCa was evaluated using consensus clustering of MRMGs in the TCGA database. Subsequently, a macrophage-related marker gene prognostic signature (MRMGPS) was constructed by LASSO-Cox regression analysis and grouped based on the median risk score. The predictive ability of MRMGPS was verified by experiments, survival analysis, and nomogram in the TCGA cohort and GEO-Merged cohort. Additionally, immune landscape, genomic heterogeneity, tumor stemness, drug sensitivity, and molecular docking were conducted to explore the relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection. Results: We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. Furthermore, we showed that the MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts. More importantly, we also found the close relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection by multi-omics analysis. Discussion: Our study reveals the application value of MRMGPS in predicting the prognosis of PCa patients. It also provides a novel perspective and theoretical basis for immune research and drug choices for PCa.

Pathogenesis to management of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer whose incidence continues to rise in many parts of the world due to a concomitant rise in many associated risk factors, such as alcohol use and obesity. Although early-stage HCC can be potentially curable through liver resection, liver-directed therapies, or transplantation, patients usually present with intermediate to advanced disease, which continues to be associated with a poor prognosis. This is because HCC is a cancer with significant complexities, including substantial clinical, histopathologic, and genomic heterogeneity. However, the scientific community has made a major effort to better characterize HCC in those aspects via utilizing tissue sampling and histological classification, whole genome sequencing, and developing viable animal models. These efforts ultimately aim to develop clinically relevant biomarkers and discover molecular targets for new therapies. For example, until recently, there was only one approved systemic therapy for advanced or metastatic HCC in the form of sorafenib. Through these efforts, several additional targeted therapies have gained approval in the United States, although much progress remains to be desired. This review will focus on the link between characterizing the pathogenesis of HCC with current and future HCC management.

A Systematic Analysis Reveals the Prognostic and Immunological Role of Reptin/RUVBL2 in Human Tumors.

Reptin/RUVBL2 is involved in the remodeling of chromatin, DNA damage repair, and regulation of the cell cycle, all of which help to play essential roles in cancer. However, relevant pan-cancer analysis of Reptin is lacking. This study first investigated the potential oncogenic roles of Reptin and revealed a relationship between Reptin with clinicopathological characteristics and immune infiltration based on big data. Here, we showed that Reptin is overexpressed in many cancers. A significant association exists between the expression of Reptin and the prognosis of cancer cases. Reptin had a meaningful interaction with the immune infiltration of CD4+ Th1 cells and immune modulator genes in multiple cancer types. And negative correlation exists between Reptin and cancer-associated fibroblasts in BRCA, PRAD, TGCT, and THYM. A significant negative association exists between Reptin and regulatory T cells in TGCT and THCA. Moreover, Reptin is significantly associated with genomic heterogeneity, DNA mismatch repair genes, methyltransferase, and RNA modification genes in specific cancer types. Spliceosome, Hippo signaling pathway, DNA replication pathway, and acetyltransferase activity-associated functions were observed in the effect of Reptin on the tumor. This systematic analysis highlights Reptin as a vital cancer regulator among numerous genes and proved its potential prognosticator value and therapeutic target role for specific tumor types.