A novel aging-associated lncRNA signature for predicting prognosis in osteosarcoma

Intra-tumoral heterogeneity assessment of the extracellular bone matrix and immune microenvironment in osteosarcoma using digital imaging to predict therapeutic response

The assessment of chemotherapy response in osteosarcoma (OS), based on the average percentage of viable cells, is limited as it overlooks the spatial heterogeneity of tumor cell response (foci of resistant cells), immune microenvironment and bone microarchitecture. Despite the resulting positive classification for response to chemotherapy, some patients experience early metastatic recurrence, demonstrating that our conventional tools for evaluating treatment response are insufficient. We studied the interactions between tumor cells, immune cells (lymphocytes, histiocytes, osteoclasts), and bone extracellular matrix (ECM) in 18 surgical resection samples of osteosarcoma using multiplex and conventional immunohistochemistry (CD8, CD163, CD68, SATB2), combined with multi-scale characterization approaches in territories of good and poor response (GRT/PRT) to treatment. GRT and PRT were defined as subregions with <10% and ≥10% of viable tumor cells, respectively. Local correlations between bone ECM porosity and density of immune cells were assessed in these territories. Immune cell density was then correlated to overall patient survival. Two patterns were identified for histiocytes and osteoclasts. In poor responder (PR) patients, CD68 osteoclast density exceeded that of CD163 histiocytes, but was not related to bone ECM load. Conversely, in good responder (GR) patients, CD163 histiocytes were more numerous than CD68 osteoclasts. For both of them, a significant negative local correlation with bone ECM porosity was found (p<0,01). Moreover, in PRT, multinucleated osteoclasts were rounded and intermingled with tumor cells, whereas in GRT they were elongated and found in close contact with bone trabeculae. CD8 levels were always low in metastatic patients and those initially considered as GR but rapidly died from their disease. The specific recruitment of histiocytes and osteoclasts within the bone ECM, and the level of CD8 represent new features of osteosarcoma response to treatment. The associated prognostic signatures should be integrated into the therapeutic stratification algorithm of patients, after surgery.

Deciphering disulfidptosis: Uncovering a lncRNA-based signature for prognostic assessment, personalized immunotherapy, and therapeutic agent selection in lung adenocarcinoma patients

BACKGROUND

Disulfidptosis, a recently identified type of regulated cell death, plays critical roles in various biological processes of cancer; however, whether they can impact the prognosis of lung adenocarcinoma (LUAD) remains to be fully elucidated. We aimed to adopt this concept to develop and validate a lncRNA signature for LUAD prognostic prediction.

METHODS

For this study, the TCGA-LUAD dataset was used as the training cohort, and multiple datasets from the GEO database were pooled as the validation cohort. Disulfidptosis regulated genes were obtained from published studies, and various statistical methods, including Kaplan-Meier (KM), Cox, and LASSO, were used to train our gene signature DISULncSig. We utilized KM analysis, COX analysis, receiver operating characteristic analysis, time-dependent AUC analysis, principal component analysis, nomogram predictor analysis, and functional assays in our validation process. We also compared DISULncSig with previous studies. We performed analyses to evaluate DISULncSig's immunotherapeutic ability, focusing on eight immune algorithms, TMB, and TIDE. Additionally, we investigated potential drugs that could be effective in treating patients with high-risk scores. Additionally qRT-PCR examined the expression patterns of DISULncSig lncRNAs, and the ability of DISULncSig in pan-cancer was also assessed.

RESULTS

DISULncSig containing twelve lncRNAs was trained and showed strong predictive ability in the validation cohort. Compared with previous similar studies, DISULncSig had more prognostic ability advantages. DISULncSig was closely related to the immune status of LUAD, and its tight relationship with checkpoints KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28 may be the key to its potential immunotherapeutic ability. For the high DISULncSig score population, we found ten drug candidates, among which epothilone-b may have the most potential. The pan-cancer analysis found that DISULncSig was a risk factor in multiple cancers. Additionally, we discovered that some of the DISULncSig lncRNAs could play crucial roles in specific cancer types.

CONCLUSION

The current study established a powerful prognostic DISULncSig signature for LUAD that was also valid for most pan-cancers. This signature could serve as a potential target for immunotherapy and might help the more efficient application of drugs to specific populations.