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Proteins overexpressed in early-stage cancers may serve as early diagnosis and prognosis markers as well as targets for cancer therapies. In this study, we examined the expression of an essential amino acid carrier SLC7A5 (LAT1, CD98, or 4F2 light chain) in cancer tissue from two well-annotated cohorts of 575 cases of early-stage and 106 cases of late-stage colorectal cancer patients. Immunohistochemistry showed SLC7A5 overexpression in 72.0% of early-stage and 56.6% of late-stage cases. SLC7A5 expression was not influenced by patient gender, age, location, or mismatch repair status, although it appeared to be slightly less prevalent in tumors of mucinous differentiation or with lymphovascular invasion. Statistical analyses revealed a positive correlation between SLC7A5 overexpression and both overall survival and disease-free survival in early-stage but not late-stage cancers. Co-expression analyses of the TCGA and CPTAC colorectal cancer cohorts identified a network of gene transcripts positively related to SLC7A5, with its heterodimer partner SLC3A2 having the highest co-expression score. Network analysis uncovered the SLC7A network to be significantly associated with ncRNA such as tRNA processing and the mitotic cell cycle. Since SLC7A5 is also a marker of activated lymphocytes such as NK, T, and B lymphocytes, SLC7A5 overexpression in early colorectal cancers might trigger a strong anti-tumor immune response which could results in better clinical outcome. Overall, our study provides clear evidence of differential SLC7A5 expression and its prognostic value for early-stage colorectal cancer, although the understanding of its functions in colorectal tumorigenesis and cancer immunity is currently rather limited and awaits further characterization. [ABSTRACT FROM AUTHOR]

Background: Analysis of omics data that contain multidimensional biological and clinical information can be complex and make it difficult to deduce significance of specific biomarker factors. Methods: We explored the utility of propensity score matching (PSM), a statistical technique for minimizing confounding factors and simplifying the examination of specific factors. We tested two datasets generated from cohorts of colorectal cancer (CRC) patients, one comprised of immunohistochemical analysis of 12 protein markers in 544 CRC tissues and another consisting of RNA-seq profiles of 163 CRC cases. We examined the efficiency of PSM by comparing pre- and post-PSM analytical results. Results: Unlike conventional analysis which typically compares randomized cohorts of cancer and normal tissues, PSM enabled direct comparison between patient characteristics uncovering new prognostic biomarkers. By creating optimally matched groups to minimize confounding effects, our study demonstrates that PSM enables robust extraction of significant biomarkers while requiring fewer cancer cases and smaller overall patient cohorts. Conclusion: PSM may emerge as an efficient and cost-effective strategy for multiomic data analysis and clinical trial design for biomarker discovery. [ABSTRACT FROM AUTHOR]

To clarify the significance of quantitative analyses of amyloid proteins in clinical practice and in research relating to systemic amyloidoses, we applied mass spectrometry–based quantification by isotope-labeled cell-free products (MS-QBIC) to formalin-fixed, paraffin-embedded (FFPE) tissues. The technique was applied to amyloid tissues collected by laser microdissection of Congo red-stained lesions of FFPE specimens. Twelve of 13 amyloid precursor proteins were successfully quantified, including serum amyloid A (SAA), transthyretin (TTR), immunoglobulin kappa light chain (IGK), immunoglobulin lambda light chain (IGL), beta-2-microglobulin (B2M), apolipoprotein (Apo) A1, Apo A4, Apo E, lysozyme, Apo A2, gelsolin, and fibrinogen alpha chain; leukocyte cell–derived chemotaxin-2 was not detected. The quantification of SAA, TTR, IGK, IGL, and B2M confirmed the responsible proteins, even when the immunohistochemical results were not decisive. Considerable amounts of Apo A1, Apo A4, and Apo E were deposited in parallel amounts with the responsible proteins. Quantification of amyloid protein by MS-QBIC is feasible and useful for the classification of and research on systemic amyloidoses. [ABSTRACT FROM AUTHOR]

Proteomic analyses indicate that STAT1 protein (signal transducer and activator of transcription 1 or transcription factor ISGF-3 components p91/p84) is upregulated in some colorectal cancers. This study examined 736 colorectal cancer patients for the expression of STAT1 protein in tissue specimens, including 614 early stage patients and 122 advanced stage patients. Tissue microarrays were constructed, and STAT1 expression was examined by immunohistochemistry and scored semi-quantitatively. Among all cases, 9% of cases displayed high levels of cytoplasmic expression of STAT1 and 15% of cases had positive nuclear expression. Based on statistical analyses of a cohort of 559 early stage patients with survival data and no neoadjuvant therapy, we found that high levels of cytoplasmic expression of STAT1 correlated with shorter survival time in early stage colorectal cancer, particularly of the microsatellite instability (MSI) subtype. Additional analysis of a 244-case cohort of colorectal cancers from the Cancer Genome Atlas found that STAT1 gene expression correlated positively with PD-L1 (CD274) and PD-1 (PDCD1) but had no correlation with KRAS or BRAF mutation status. STAT1 expression showed no clear correlation with any of the 4 clinical diagnostic markers of mismatch repair, MLH1, MSH2, MSH6, and PMS2, suggesting its potential as an independent outcome marker for MSI cancers. Our findings suggest that STAT1 may be used as a potential prognostic protein marker for stratifying the outcome risk of early stage MSI colorectal cancer. [ABSTRACT FROM AUTHOR]

Autoantigens are the molecular targets in autoimmune diseases. They are a cohort of seemingly unrelated self-molecules present in different parts of the body, yet they can trigger a similar chain of autoimmune responses such as autoantibody production. We previously reported that dermatan sulfate (DS) can bind self-molecules of dying cells to stimulate autoreactive CD5+ B cells to produce autoantibodies. The formation of autoantigen-DS complexes converts the normally non-antigenic self-molecules to none-self antigens, and thus DS-affinity represents a common underlying biochemical property for autoantigens. This study sought to apply this property to identify potential autoantigens in the kidney. Total proteins were extracted from mouse kidney tissues and loaded onto DS-Sepharose resins. Proteins without affinity were washed off the resins, whereas those with increasing DS-affinity were eluted with step gradients of increasing salt strength. Fractions with strong and moderate DS-affinity were sequenced by mass spectrometry and yielded 25 and 99 proteins, respectively. An extensive literature search was conducted to validate whether these had been previously reported as autoantigens. Of the 124 proteins, 79 were reported autoantigens, and 19 out of 25 of the strong-DS-binding ones were well-known autoantigens. Moreover, these proteins largely fell into the two most common autoantibody categories in autoimmune kidney diseases, including 40 ANA (anti-nuclear autoantibodies) and 25 GBM (glomerular basement membrane) autoantigens. In summary, this study compiles a large repertoire of potential autoantigens for autoimmune kidney diseases. This autoantigen-ome sheds light on the molecular etiology of autoimmunity and further supports our hypothesis DS-autoantigen complexes as a unifying principle of autoantigenicity. [ABSTRACT FROM AUTHOR]