Prognostic Impact of Sarcopenia in Patients with Metastatic Hormone-Sensitive Prostate Cancer.

The clinical value of sarcopenia has not been determined yet in metastatic hormone-sensitive prostate cancer (mHSPC). We retrospectively evaluated data of 70 consecutive patients with mHSPC receiving treatment with either early docetaxel (n = 42) or abiraterone acetate (n = 28) between July 2018 and April 2021. Skeletal muscle index was calculated from cross-sectional areas of skeletal muscle on baseline computed tomography (CT), defining sarcopenia as a skeletal muscle index of ≤52.4 cm2/m2. Failure-free survival (FFS), radiographic progression-free survival, and time to prostate-specific antigen (PSA) progression were estimated using the Kaplan-Meier method, and differences in survival probability were compared using the log-rank test. Cox proportional hazards regression analysis was conducted to identify the predictors of clinical outcomes. Patients with sarcopenia (n = 47) had shorter FFS than those without sarcopenia (n = 23) (median, 20.1 months vs. not reached; log-rank p < 0.001). Sarcopenia was independently associated with shorter FFS (hazard ratio (HR), 6.69; 95% confidence interval (CI), 1.57-28.49; p = 0.010) and time to PSA progression (HR, 12.91; 95% CI, 1.08-153.85; p = 0.043). In conclusion, sarcopenia is an independent prognostic factor for poor FFS and time to PSA progression in patients with mHSPC who receive early docetaxel or abiraterone acetate treatment.

Dynamics of Genomic, Epigenomic, and Transcriptomic Aberrations during Stepwise Hepatocarcinogenesis.

Hepatocellular carcinoma (HCC) undergoes a stepwise progression from liver cirrhosis to low-grade dysplastic nodule (LGDN), high-grade dysplastic nodule (HGDN), early HCC (eHCC), and progressed HCC (pHCC). Here, we profiled multilayered genomic, epigenomic, and transcriptomic aberrations in the stepwise hepatocarcinogenesis. Initial DNA methylation was observed in eHCC (e.g., DKK3, SALL3, and SOX1) while more extensive methylation was observed in pHCC. In addition, eHCCs showed an initial loss of DNA copy numbers of tumor suppressor genes in the 4q and 13q regions, thereby conferring survival benefits to cancer cells. Transcriptome analysis revealed that HGDNs expressed endoplasmic reticulum (ER) stress-related genes, while eHCC started to express oncogenes. Furthermore, integrative analysis indicated that expression of the serine peptidase inhibitor, Kazal type 1 (SPINK1), played a pivotal role in eHCC development. Significant demethylation of SPINK1 was observed in eHCC compared to HGDN. The study also demonstrated that ER stress may induce SPINK1 demethylation and expression in liver cancer cells. In conclusion, these results reveal the dynamics of multiomic aberrations during malignant conversion of liver cancer, thus providing novel pathobiological insights into hepatocarcinogenesis. SIGNIFICANCE: Multiomics profiling and integrative analyses of stepwise hepatocarcinogenesis reveal novel mechanistic and clinical insights into hepatocarcinogenesis.

Transcriptomic and histopathological analysis of cholangiolocellular differentiation trait in intrahepatic cholangiocarcinoma.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinoma (iCCA) is a heterogeneous entity with diverse aetiologies, morphologies and clinical outcomes. Recently, histopathological distinction of cholangiolocellular differentiation (CD) of iCCA has been suggested. However, its genome-wide molecular features and clinical significance remain unclear. METHODS: Based on CD status, we stratified iCCAs into iCCA with CD (n=20) and iCCA without CD (n=102), and performed an integrative analysis using transcriptomic and clinicopathological profiles. RESULTS: iCCA with CD revealed less aggressive histopathological features compared to iCCA without CD, and iCCA with CD showed favourable clinical outcomes of overall survival and time to recurrence than iCCA without CD (P<.05 for all). Transcriptomic profiling revealed that iCCA with CD resembled an inflammation-related subtype, while iCCA without CD resembled a proliferation subtype. In addition, we identified a CD signature that can predict prognostic outcomes of iCCA (CD_UP, n=486 and CD_DOWN, n=308). iCCAs were subgrouped into G1 (positivity for CRP and CDH2, 7%), G3 (positivity for S100P and TFF1, 32%) and G2 (the others, 61%). Prognostic outcomes for overall survival (P=.001) and time to recurrence (P=.017) were the most favourable in G1-iCCAs, intermediate in G2-iCCAs and the worst in G3-iCCAs. Similar result was confirmed in the iCCA set from GSE26566 (n=68). CONCLUSIONS: CD signature was identified to predict the prognosis of iCCA. The combined evaluation of histology of CD and protein expression status of CRP, CDH2, TFF1 and S100P might help subtyping and predicting clinical outcomes of iCCA.

Integrative analysis of genomic and epigenomic regulation of the transcriptome in liver cancer.

Hepatocellular carcinoma harbors numerous genomic and epigenomic aberrations of DNA copy numbers and DNA methylation. Transcriptomic deregulation by these aberrations plays key driver roles in heterogeneous progression of cancers. Here, we profile DNA copy numbers, DNA methylation, and messenger RNA expression levels from 64 cases of hepatocellular carcinoma specimens. We find that the frequencies of the aberrancies of the DNA copy-number-correlated (CNVcor) expression genes and the methylation-correlated expression (METcor) genes are co-regulated significantly. Multi-omics integration of the CNVcor and METcor genes reveal three prognostic subtypes of hepatocellular carcinoma, which can be validated by an independent data. The most aggressive subtype expressing stemness genes has frequent BAP1 mutations, implying its pivotal role in the aggressive tumor progression. In conclusion, our integrative analysis of genomic and epigenomic regulation provides new insights on the multi-layered pathobiology of hepatocellular carcinoma, which might be helpful in developing precision management for hepatocellular carcinoma patients.Hepatocellular carcinoma is known to harbour numerous genomic and epigenomic aberrations, driving transcriptomic deregulation. Here, the authors integrate genomic, epigenomic, and expression data to reveal three prognostic subtypes, providing insight to the pathobiology of hepatocellular carcinoma.

Identification of a mitochondrial defect gene signature reveals NUPR1 as a key regulator of liver cancer progression.

UNLABELLED: Many cancer cells require more glycolytic adenosine triphosphate production due to a mitochondrial respiratory defect. However, the roles of mitochondrial defects in cancer development and progression remain unclear. To address the role of transcriptomic regulation by mitochondrial defects in liver cancer cells, we performed gene expression profiling for three different cell models of mitochondrial defects: cells with chemical respiratory inhibition (rotenone, thenoyltrifluoroacetone, antimycin A, and oligomycin), cells with mitochondrial DNA depletion (Rho0), and liver cancer cells harboring mitochondrial defects (SNU354 and SNU423). By comparing gene expression in the three models, we identified 10 common mitochondrial defect-related genes that may be responsible for retrograde signaling from cancer cell mitochondria to the intracellular transcriptome. The concomitant expression of the 10 common mitochondrial defect genes is significantly associated with poor prognostic outcomes in liver cancers, suggesting their functional and clinical relevance. Among the common mitochondrial defect genes, we found that nuclear protein 1 (NUPR1) is one of the key transcription regulators. Knockdown of NUPR1 suppressed liver cancer cell invasion, which was mediated in a Ca(2+) signaling-dependent manner. In addition, by performing an NUPR1-centric network analysis and promoter binding assay, granulin was identified as a key downstream effector of NUPR1. We also report association of the NUPR1-granulin pathway with mitochondrial defect-derived glycolytic activation in human liver cancer. CONCLUSION: Mitochondrial respiratory defects and subsequent retrograde signaling, particularly the NUPR1-granulin pathway, play pivotal roles in liver cancer progression.

Molecular classification of basal cell carcinoma of skin by gene expression profiling.

Non-melanoma skin cancers (NMSC) including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are more common kinds of skin cancer. Although these tumors share common pathological and clinical features, their similarity and heterogeneity at molecular levels are not fully elaborated yet. Here, by performing comparative analysis of gene expression profiling of BCC, SCC, and normal skin tissues, we could classify the BCC into three subtypes of classical, SCC-like, and normal-like BCCs. Functional enrichment and pathway analyses revealed the molecular characteristics of each subtype. The classical BCC showed the enriched expression and transcription signature with the activation of Wnt and Hedgehog signaling pathways, which were well known key features of BCC. By contrast, the SCC-like BCC was enriched with immune-response genes and oxidative stress-related genes. Network analysis revealed the PLAU/PLAUR as a key regulator of SCC-like BCC. The normal-like BCC showed prominent activation of metabolic processes particularly the fatty acid metabolism. The existence of these molecular subtypes could be validated in an independent dataset, which demonstrated the three subgroups of BCC with distinct functional enrichment. In conclusion, we suggest a novel molecular classification of BCC providing insights on the heterogeneous progression of BCC.

Perspectives of integrative cancer genomics in next generation sequencing era.

The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.