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Background Serous ovarian carcinoma is the most frequent histological subgroup of ovarian cancer and the leading cause of death among gynecologic tumors. The tumor microenvironment and cancer-associated fibroblasts (CAFs) have a critical role in the origin and progression of cancer. We comprehensively characterized the crosstalk between CAFs and ovarian cancer cells from malignant fluids to identify specific ligands and receptors mediating intercellular communications and disrupted pathways related to prognosis and therapy response. Methods Malignant fluids of serous ovarian cancer, including tumor-derived organoids, CAFs-enriched (eCAFs), and malignant effusion cells (no cultured) paired with normal ovarian tissues, were explored by RNA-sequencing. These data were integrated with single-cell RNA-sequencing data of ascites from ovarian cancer patients. The most relevant ligand and receptor interactions were used to identify differentially expressed genes with prognostic values in ovarian cancer. Results CAF ligands and epithelial cancer cell receptors were enriched for PI3K-AKT, focal adhesion, and epithelial-mesenchymal transition signaling pathways. Collagens, MIF, MDK, APP, and laminin were detected as the most significant signaling, and the top ligand-receptor interactions THBS2/THBS3 (CAFs)—CD47 (cancer cells), MDK (CAFs)—NCL/SDC2/SDC4 (cancer cells) as potential therapeutic targets. Interestingly, 34 genes encoding receptors and ligands of the PI3K pathway were associated with the outcome, response to treatment, and overall survival in ovarian cancer. Up-regulated genes from this list consistently predicted a worse overall survival (hazard ratio > 1.0 and log-rank P  < 0.05) in two independent validation cohorts. Conclusions This study describes critical signaling pathways, ligands, and receptors involved in the communication between CAFs and cancer cells that have prognostic and therapeutic significance in ovarian cancer. AKQp7fCjRyS9LmaGP7R5S5 Video abstract

Background Computed tomographies (CT) are useful for identifying muscle loss in non-small lung cancer (NSCLC) cachectic patients. However, we lack consensus on the best cutoff point for pectoralis muscle loss. We aimed to characterize NSCLC patients based on muscularity, clinical data, and the transcriptional profile from the tumor microenvironment to build a cachexia classification model. Methods We used machine learning to generate a muscle loss prediction model, and the tumor's cellular and transcriptional profile was characterized in patients with low muscularity. First, we measured the pectoralis muscle area (PMA) of 211 treatment-naive NSCLC patients using CT available in The Cancer Imaging Archive. The cutoffs were established using machine learning algorithms (CART and Cutoff Finder) on PMA, clinical, and survival data. We evaluated the prediction model in a validation set (36 NSCLC). Tumor RNA-Seq (GSE103584) was used to profile the transcriptome and cellular composition based on digital cytometry. Results CART demonstrated that a lower PMA was associated with a high risk of death (HR = 1.99). Cutoff Finder selected PMA cutoffs separating low-muscularity (LM) patients based on the risk of death ( P -value = 0.003; discovery set). The cutoff presented 84% of success in classifying low muscle mass. The high risk of LM patients was also found in the validation set. Tumor RNA-Seq revealed 90 upregulated secretory genes in LM that potentially interact with muscle cell receptors. The LM upregulated genes enriched inflammatory biological processes. Digital cytometry revealed that LM patients presented high proportions of cytotoxic and exhausted CD8+ T cells. Conclusions Our prediction model identified cutoffs that distinguished patients with lower PMA and survival with an inflammatory and immunosuppressive TME enriched with inflammatory factors and CD8+ T cells.

Fish muscle growth is a complex process regulated by multiple pathways, resulting on the net accumulation of proteins and the activation of myogenic progenitor cells. Around 350–320 million years ago, teleost fish went through a specific whole genome duplication (WGD) that expanded the existent gene repertoire. Duplicated genes can be retained by different molecular mechanisms such as subfunctionalization, neofunctionalization or redundancy, each one with different functional implications. While the great majority of ohnolog genes have been identified in the teleost genomes, the effect of gene duplication in the fish physiology is still not well characterized. In the present study we studied the effect of WGD on the transcription of the duplicated components controlling muscle growth. We compared the expression of lineage-specific ohnologs related to myogenesis and protein balance in the fast-skeletal muscle of pacus ( Piaractus mesopotamicus —Ostariophysi) and Nile tilapias ( Oreochromis niloticus —Acanthopterygii) fasted for 4 days and refed for 3 days. We studied the expression of 20 ohnologs and found that in the great majority of cases, duplicated genes had similar expression profiles in response to fasting and refeeding, indicating that their functions during growth have been conserved during the period after the WGD. Our results suggest that redundancy might play a more important role in the retention of ohnologs of regulatory pathways than initially thought. Also, comparison to non-duplicated orthologs showed that it might not be uncommon for the duplicated genes to gain or loss new regulatory elements simultaneously. Overall, several of duplicated ohnologs have similar transcription profiles in response to pro-growth signals suggesting that evolution tends to conserve ohnolog regulation during muscle development and that in the majority of ohnologs related to muscle growth their functions might be very similar.

Background Cachexia is a multifactorial syndrome highly associated with specific tumour types, but the causes of variation in cachexia prevalence and severity are unknown. While circulating plasma mediators (soluble cachectic factors) derived from tumours have been implicated with the pathogenesis of the syndrome, these associations were generally based on plasma concentration rather than tissue‐specific gene expression levels. Here, we hypothesized that tumour gene expression profiling of cachexia‐inducing factors (CIFs) in human cancers with different prevalence of cachexia could reveal potential cancer‐specific cachexia mediators and biomarkers of clinical outcome. Methods First, we combined uniformly processed RNA sequencing data from The Cancer Genome Atlas and Genotype‐Tissue Expression databases to characterize the expression profile of secretome genes in 12 cancer types (4651 samples) compared with their matched normal tissues (2737 samples). We systematically investigated the transcriptomic data to assess the tumour expression profile of 25 known CIFs and their predictive values for patient survival. We used the Xena Functional Genomics tool to analyse the gene expression of CIFs according to neoplastic cellularity in pancreatic adenocarcinoma, which is known to present the highest prevalence of cachexia. Results A comprehensive characterization of the expression profiling of secreted genes in different human cancers revealed pathways and mediators with a potential role in cachexia within the tumour microenvironment. Cytokine‐related and chemokine‐related pathways were enriched in tumour types frequently associated with the syndrome. CIFs presented a tumour‐specific expression profile, in which the number of upregulated genes was correlated with the cachexia prevalence (r2: 0.80; P value: 0.002) and weight loss (r2: 0.81; P value: 0.002). The distinct gene expression profile, according to tumour type, was significantly associated with prognosis (P value ≤ 1.96 E‐06). In pancreatic adenocarcinoma, the upregulated CIF genes were associated with tumours presenting low neoplastic cellularity and high leucocyte fraction and not with tumour grade. Conclusions Our results present a biological dimension of tumour‐secreted elements that are potentially useful to explain why specific cancer types are more likely to develop cachexia. The tumour‐specific profile of CIFs may help the future development of better targeted therapies to treat cancer types highly associated with the syndrome.

Background Cancer is extensively studied, yet its origins and progression remain unclear. A key question is why tumors of the same type vary in aggressiveness and treatment response. In colorectal cancer (CRC), the third most common cancer, this variability led to the identification of molecular subtypes (CMS). However, the tumor microenvironment remains poorly understood and may be crucial for understanding carcinogenesis and drug resistance. A promising approach is analyzing cell interactions through ligand-receptor expression. This study used bioinformatics to examine CRC in different anatomical locations, identify diagnostic and prognostic biomarkers, and propose targeted drugs. Methods Expression data were obtained from the TCGA-COAD database. All samples were filtered based on the tumor’s region of origin and purity. RNA-seq expression analysis was then conducted to assess molecular differences according to tumor location and purity, identifying region-specific ligands and receptors using the secretome list as a reference. Once these differences were identified, an interactome was constructed to depict cell interactions within the tumor microenvironment. The most relevant genes were then evaluated for their prognostic potential through survival analysis, and their susceptibility to pharmacological modulation was assessed to identify potential new drug candidates for CRC treatment. Results The integration of secretome data and the construction of the interactome proved to be a valuable approach for detecting novel biomarkers specific to right- and left-sided CRC. Through this approach, FGFR4 , FLT1 , and WNT5A were identified as key biomarkers involved in tumor carcinogenesis, modulating distinct processes in each region, such as fibroblast recruitment and cell division. Based on these biomarkers, Dovitinib and Nintedanib were predicted as potential therapeutic agents, as they target multiple identified markers. Conclusion This study highlights FGFR4 , FLT1 , and WNT5A as key diagnostic and therapeutic biomarkers for CRC, with their relevance varying based on the tumor’s site of origin. Leveraging these findings, we propose Dovitinib and Nintedanib as promising targeted therapies for CRC. These insights can enhance current treatment strategies and pave the way for future in vivo and in vitro studies, driving progress in CRC research and therapy.

To gain insight on the impact of preventive exercise during pulmonary arterial hypertension (PAH), we evaluated the gene expression of myosins and gene-encoding proteins associated with the extracellular matrix remodeling of right hypertrophied ventricles. We used 32 male Wistar rats, separated in four groups: Sedentary Control (S, n = 8); Control with Training (T, n = 8); Sedentary with Pulmonary Arterial Hypertension (SPAH, n = 8); and Pulmonary Arterial Hypertension with Training (TPAH, n = 8). All rats underwent a two-week adaptation period; T and TPAH group rats then proceeded to an eight-week training period on a treadmill. At the beginning of the 11th week, S and T groups received an intraperitoneal injection of saline, and SPAH and TPAH groups received an injection of monocrotaline (60 mg/kg). Rats in the T and TPAH groups then continued with the training protocol until the 13th week. We assessed exercise capacity, echocardiography analysis, Fulton’s index, cross-sectional areas of cardiomyocytes, collagen content and types, and fractal dimension (FD). Transcript abundance of myosins and extracellular matrix genes were estimated through reverse transcription-quantitative PCR (RT-qPCR). When compared to the SPAH group, the TPAH group showed increases in functional capacity and pulmonary artery acceleration time/pulmonary ejection time ratio and decreases in Fulton’s index and cross-sectional areas of myocyte cells. However, preventive exercise did not induce alterations in col1a1 and myh7 gene expression. Our findings demonstrate that preventive exercise improved functional capacity, reduced cardiac hypertrophy, and attenuated PH development without interfering in mRNA-encoding myosin and collagen expression during PAH.

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

The number of visible ovarian antral follicles (antral follicle count-AFC) is repeatable in bovine individuals, but highly variable between animals, and with differences between Bos taurus and Bos indicus breeds. Several studies have tried to determine the correlation between AFC and increased fertility in cattle. While the impacts of AFC on embryo production, hormonal levels, and pregnancy rates have been described, the molecular effects of AFC on bovine oviducts have not yet been investigated. Here, the aim was to investigate the impact of breeds, such as Aberdeen Angus and Nelore heifer with high or low AFC, on abundance of transcripts and protein related to oviductal transport, sperm reservoir formation, monospermy control, and gamete interaction in the oviducts. In summary, the ovulation side was the major factor that affected transcript abundance on bovine oviducts. However, a discreet effect among AFC and cattle breeds was also observed. Based on this, we concluded and reinforced here that differential microenvironments between ipsilateral and contralateral oviducts have a major effect on modulating the transcripts related to oviductal transport, sperm reservoir formation, monospermy control, and gamete interaction. However, we cannot exclude that there is minimal effect of AFC or breed on regulation of some genes (such as AGTR1, ACE1, FUCA1, and VEGFA) in bovine oviducts.

Pacu (Piaractus mesopotamicus) is a Brazilian fish with a high economic value in pisciculture due to its rusticity and fast growth. Postnatal growth of skeletal muscle in fish occurs by hyperplasia and/or hypertrophy, processes that are dependent on the proliferation and differentiation of myoblasts. A class of small noncoding RNAs, known as microRNAs (miRNAs), represses the expression of target mRNAs, and many studies have demonstrated that miR-1, miR-133, miR-206 and miR-499 regulate different processes in skeletal muscle through the mRNA silencing of hdac4 (histone deacetylase 4), srf (serum response factor), pax7 (paired box 7) and sox6 ((sex determining region Y)-box 6), respectively. The aim of our work was to evaluate the expression of these miRNAs and their putative target mRNAs in fast- and slow-twitch skeletal muscle of pacu during growth. We used pacus in three different development stages: larval (aged 30 days), juvenile (aged 90 days and 150 days) and adult (aged 2 years). To complement our study, we also performed a pacu myoblast cell culture, which allowed us to investigate miRNA expression in the progression from myoblast proliferation to differentiation. Our results revealed an inverse correlation between the expression of the miRNAs and their target mRNAs, and there was evidence that miR-1 and miR-206 may regulate the differentiation of myoblasts, whereas miR-133 may regulate the proliferation of these cells. miR-499 was highly expressed in slow-twitch muscle, which suggests its involvement in the specification of the slow phenotype in muscle fibers. The expression of these miRNAs exhibited variations between different development stages and between distinct muscle twitch phenotypes. This work provides the first identification of miRNA expression profiles in pacu skeletal muscle and suggests an important role of these molecules in muscle growth and in the maintenance of the muscle phenotype.

Here, we analyzed the fast-twitch muscle of juvenile Piaractus mesopotamicus (pacu) submitted to prolonged fasting (30d) and refeeding (6h, 24h, 48h and 30d). We measured the relative rate of weight and length increase (RRIlength and RRIweight), performed shotgun proteomic analysis and did Western blotting for PVALB after 30d of fasting and 30d of refeeding. We assessed the gene expression of igf-1, mafbx and pvalb after 30d of fasting and after 6h, 24h, 48h and 30d of refeeding. We performed a bioinformatic analysis to predict miRNAs that possibly control parvalbumin expression. After fasting, RRIlength, RRIweight and igf-1 expression decreased, while the mafbx expression increased, which suggest that prolonged fasting caused muscle atrophy. After 6h and 24h of refeeding, mafbx was not changed and igf-1 was downregulated, while after 48h of refeeding mafbx was downregulated and igf-1 was not changed. After 30d of refeeding, RRIlength and RRIweight were increased and igf-1 and mafbx expression were not changed. Proteomic analysis identified 99 proteins after 30d of fasting and 71 proteins after 30d of refeeding, of which 23 and 17, respectively, were differentially expressed. Most of these differentially expressed proteins were related to cytoskeleton, muscle contraction, and metabolism. Among these, parvalbumin (PVALB) was selected for further validation. The analysis showed that pvalb mRNA was downregulated after 6h and 24h of refeeding, but was not changed after 30d of fasting or 48h and 30d of refeeding. The Western blotting confirmed that PVALB protein was downregulated after 30d of fasting and 30d of refeeding. The downregulation of the protein and the unchanged expression of the mRNA after 30d of fasting and 30d of refeeding suggest a post-transcriptional regulation of PVALB. Our miRNA analysis predicted 444 unique miRNAs that may target pvalb. In conclusion, muscle atrophy and partial compensatory growth caused by prolonged fasting followed by refeeding affected the muscle proteome and PVALB expression.