Molecular characteristics and prognostic significances of lysosomal-dependent cell death in kidney renal clear cell carcinoma

Lysosomal-dependent cell death (LDCD) has an excellent therapeutic effect on apoptosis-resistant and drug-resistant tumors; however, the important role of LDCD-related genes (LDCD-RGs) in kidney renal clear cell carcinoma (KIRC) has not been reported. Initially, single-cell atlas of LDCD signal in KIRC was comprehensively depicted. We also emphasized the molecular characteristics of LDCD-RGs in various human neoplasms. Predicated upon the expressive quotients of LDCD-RGs, we stratified KIRC patients into tripartite cohorts denoted as C1, C2, and C3. Those allocated to the ambit of C1 evinced the most sanguine prognosis within the KIRC cohort, underscored by the acme of LDCD-RGs scores. This further confirms the significant role that LDCD-RGs play in both the pathophysiological foundation and clinical implications of KIRC. In culmination, by virtue of employing the LASSO-Cox analytical modality, we have ushered in an innovative and avant-garde prognostic framework tailored for KIRC, predicated on the bedrock of LDCD-RGs. The assemblage of KIRC instances was arbitrarily apportioned into constituents inclusive of a didactic cohort, an internally wielded validation cadre, and an externally administered validation cohort. Concurrently, patients were dichotomized into strata connoting elevated jeopardy synonymous with adverse prognostic trajectories, and conversely, diminished risk tantamount to favorable prognoses, contingent on the calibrated expressions of LDCD-RGs. Succinctly, our investigative findings serve to underscore the cardinal capacity harbored by LDCD-RGs within the KIRC milieu, concurrently birthing a pioneering prognostic schema intrinsically linked to the trajectory of KIRC and its attendant prognoses.

Autophagy-related long non-coding RNA signature for potential prognostic biomarkers of patients with cervical cancer: a study based on public databases

Background

Metastasis and recurrence are the main causes of death from cervical cancer (CC), thus it is important to identify more effective biomarkers to improve its prognosis. The purpose of our research was to determine the potential role of autophagy-related long non-coding RNA (lncRNA) in CC and to construct an autophagy-related lncRNA signature for survival of CC.

Methods

The lncRNAs in CC were downloaded from The Cancer Genome Atlas (TCGA) database, and autophagy-related lncRNAs were identified through the co-expression of lncRNA genes and autophagy genes. Several autophagy-related lncRNAs with prognostic value (AC012306.2, AL109976.1, ATP2A1-AS1, ILF3-DT, Z83851.2, STARD7-AS1, AC099343.2, AC008771.1, DBH-AS1, and AC097468.3) were identified using univariate and multivariate Cox regression analyses and a prognostic signature was established. The signature effect was detected by univariate Cox regression analysis [hazard ratio (HR) =1.665; 95% confidence interval (CI): 1.331–2.082; P<0.001] and multivariate Cox regression analysis (HR =1.738; 95% CI: 1.359–2.223; P<0.001). A nomogram was drawn by risk score and clinical features.

Results

The prognostic signature could predict the survival of CC by survival-receiver operating characteristic (ROC) curve [area under the curve (AUC) =0.810]. A nomogram was drawn by risk score and clinical features, and its c-index and calibration curve demonstrated that the prognostic signature could independently predict the prognosis of CC (P<0.001). Gene set enrichment analysis (GSEA) confirmed that the genes were significantly enriched in cancer- and autophagy-related pathways (P<0.05).

Conclusions

This 10 autophagy-related lncRNA signature has prognostic potential for CC. More important roles in the CC biology of these lncRNAs may be identified with further study.

A 17-gene expression-based prognostic signature associated with the prognosis of patients with breast cancer: A STROBE-compliant study

Identification of reliable predictive biomarkers for patients with breast cancer (BC).Univariate Cox proportional hazards regression model was conducted to identify genes correlated with the overall survival (OS) of patients in the TCGA-BRCA cohort. Functional enrichment analysis was conducted to investigate the biological meaning of these survival related genes. Then, patients in TCGA-BCRA were randomly divided into training set and test. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was performed and the risk score of BC patients in this model was used to build a prognostic signature. The prognostic performance of the signature was evaluated in the training set, test set, and an independent validation set GSE7390.2519 genes were demonstrated to be significantly associated with the OS of BC patients. Functional annotation of the 2519 genes suggested that these genes were associated with immune response and protein synthesis related gene ontology terms and pathways. 17 genes were identified in the LASSO Cox regression model and used to construct a 17-gene signature. Patients in the 17-gene signature low risk group have better OS and event-free survival compared with those in the 17-gene signature high risk group in the TCGA-BRCA cohort. The prognostic role of the 17-gene signature has been confirmed in the validation cohort. Multivariable Cox proportional hazards regression model suggested the 17-gene signature was an independent prognostic factor in BC.The 17-gene signature we developed could successfully classify patients into high- and low-risk groups, indicating that it might serve as candidate biomarker in BC.

Fractionated irradiation-induced EMT-like phenotype conferred radioresistance in esophageal squamous cell carcinoma

The efficacy of radiotherapy, one major treatment modality for esophageal squamous cell carcinoma (ESCC) is severely attenuated by radioresistance. Epithelial-to-mesenchymal transition (EMT) is a cellular process that determines therapy response and tumor progression. However, whether EMT is induced by ionizing radiation and involved in tumor radioresistance has been less studied in ESCC. Using multiple fractionated irradiation, the radioresistant esophageal squamous cancer cell line KYSE-150R had been established from its parental cell line KYSE-150. We found KYSE-150R displayed a significant EMT phenotype with an elongated spindle shape and down-regulated epithelial marker E-cadherin and up-regulated mesenchymal marker N-cadherin in comparison with KYSE-150. Furthermore, KYSE-150R also possessed some stemness-like properties characterized by density-dependent growth promotion and strong capability for sphere formation and tumorigenesis in NOD-SCID mice. Mechanical studies have revealed that WISP1, a secreted matricellular protein, is highly expressed in KYSE-150R and mediates EMT-associated radioresistance both in ESCC cells and in xenograft tumor models. Moreover, WISP1 has been demonstrated to be closely associated with the EMT phenotype observed in ESCC patients and to be an independent prognosis factor of ESCC patients treated with radiotherapy. Our study highlighted WISP1 as an attractive target to reverse EMT-associated radioresistance in ESCC and can be used as an independent prognostic factor of patients treated with radiotherapy.