Clinical and molecular assessment of an onco-immune signature with prognostic significance in patients with colorectal cancer

Single episode of moderate to severe traumatic brain injury leads to chronic neurological deficits and Alzheimer's-like pathological dementia

Traumatic brain injury (TBI) is one of the foremost causes of disability and mortality globally. While the scientific and medical emphasis is to save lives and avoid disability during acute period of injury, a severe health problem can manifest years after injury. For instance, TBI increases the risk of cognitive impairment in the elderly. Remote TBI history was reported to be a cause of the accelerated clinical trajectory of Alzheimer's disease-related dementia (ADRD) resulting in earlier onset of cognitive impairment and increased AD-associated pathological markers like greater amyloid deposition and cortical thinning. It is not well understood whether a single TBI event may increase the risk of dementia. Moreover, the cellular signaling pathways remain elusive for the chronic effects of TBI on cognition. We have hypothesized that a single TBI induces sustained neuroinflammation and disrupts cellular communication in a way that results later in ADRD pathology. To test this, we induced TBI in young adult CD1 mice and assessed the behavioral outcomes after 11 months followed by pathological, histological, transcriptomic, and MRI assessment. On MRI scans, these mice showed significant loss of tissue, reduced CBF, and higher white matter injury compared to sham mice. We found these brains showed progressive atrophy, markers of ADRD, sustained astrogliosis, loss of neuronal plasticity, and growth factors even after 1-year post-TBI. Because of progressive neurodegeneration, these mice had motor deficits, showed cognitive impairments, and wandered randomly in open field. We, therefore, conclude that progressive pathology after adulthood TBI leads to neurodegenerative conditions such as ADRD and impairs neuronal functions.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Exploring the potential mechanisms of Yi-Yi-Fu-Zi-Bai-Jiang-San therapy on the immune-inflamed phenotype of colorectal cancer via combined network pharmacology and bioinformatics analyses

BACKGROUND

The development and progression of colorectal cancer (CRC) is closely associated with its complex tumor microenvironment (TME). Assessment of the modified pattern of immune cell infiltration (ICI) will help increase knowledge regarding the characteristics of TME infiltration. Yi-Yi-Fu-Zi-Bai-Jiang-San (YYFZBJS) has been shown to have positive effects on the regulation of the immune microenvironment of CRC. However, its pharmacological targets and molecular mechanisms remain to be elucidated.

METHODS

Network pharmacological analysis was used to identify the target of YYFZBJS in the TME of CRC. Patients with the immune-inflamed phenotype (IIP) were identified using CRC samples from The Cancer Genome Atlas (TCGA) database. Consensus genes were identified by intersecting YYFZBJS targets, CRC disease targets and differentially expressed genes in the CRC microenvironment. Then, least absolute shrinkage and selection operator (LASSO) Cox analyses were used to identify a prognostic signature from the consensus genes. Cytoscape software was further used to build a unique herb-compound-target network diagram of the important components of YYFZBJS and prognostic gene targets. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed using the prognostic gene sets to explore the molecular mechanism of the prognostic genes in drug therapy for CRC IIP patients. Finally, single-cell analysis was performed to validate the expression of the prognostic genes in the TME of CRC using the TISCH2 database.

RESULTS

A total of 284 IIP patients were identified from 480 patients with CRC. A total of 35 consensus genes were identified as targets of YYFZBJS in the TME of CRC patients. An eleven-gene prognostic signature, including PIK3CG, C5AR1, PRF1, CAV1, HPGDS, PTGS2, SERPINE1, IDO1, TGFB1, CXCR2 and MMP9, was identified from the consensus genes, with areas under the receiver operating characteristic (ROC) curve (AUCs) values of 0.84 and 0.793 for the training and test cohorts, respectively. In the herb-compound-target network, twenty-four compounds were shown to interact with the 11 prognostic genes, which were significantly enriched in the IL-17 signaling, arachidonic acid metabolism and metabolic pathways. Single-cell analysis of the prognostic genes confirmed that their abnormal expression was associated with the TME of CRC.

CONCLUSION

This study organically integrated network pharmacology and bioinformatics analyses to identify prognostic genes in CRC IIP patients from the targets of YYFZBJS. Although this data mining work was limited to the study of mechanisms related to prognosis based on the immune microenvironment, the methodology provides new perspectives in the search for novel therapeutic targets of traditional Chinese medicines (TCMs) and accurate diagnostic indicators of cancers targeted by TCMs.

Primary Colorectal Tumor Displays Differential Genomic Expression Profiles Associated with Hepatic and Peritoneal Metastases

BACKGROUND

Despite improvements in characterization of CRC heterogeneity, appropriate risk stratification tools are still lacking in clinical practice. This study aimed to elucidate the primary tumor transcriptomic signatures associated with distinct metastatic routes.

METHODS

Primary tumor specimens obtained from CRC patients with either isolated LM (CRC-Liver) or PM (CRC-Peritoneum) were analyzed by transcriptomic mRNA sequencing, gene set enrichment analyses (GSEA) and immunohistochemistry. We further assessed the clinico-pathological associations and prognostic value of our signature in the COAD-TCGA independent cohort.

RESULTS

We identified a significantly different distribution of Consensus Molecular Subtypes between CRC-Liver and CRC-peritoneum groups. A transcriptomic signature based on 61 genes discriminated between liver and peritoneal metastatic routes. GSEA showed a higher expression of immune response and epithelial invasion pathways in CRC-Peritoneum samples and activation of proliferation and metabolic pathways in CRC-Liver samples. The biological relevance of RNA-Seq results was validated by the immunohistochemical expression of three significantly differentially expressed genes (ACE2, CLDN18 and DUSP4) in our signature. In silico analysis of the COAD-TCGA showed that the CRC-Peritoneum signature was associated with negative prognostic factors and poor overall and disease-free survivals.

CONCLUSIONS

CRC primary tumors spreading to the liver and peritoneum display significantly different transcriptomic profiles. The implementation of this signature in clinical practice could contribute to identify new therapeutic targets for stage IV CRC and to define individualized follow-up programs in stage II-III CRC.

The angiogenic genes predict prognosis and immune characteristics in esophageal squamous cell carcinoma: Evidence from multi-omics and experimental verification

Esophageal squamous cell carcinomas (ESCC) is an aggressive disease with five-year overall survival (OS) <15%. The main cause is metastasis rather than local tumor, and angiogenesis plays an important role. Angiogenesis has a significant impact on tumor metastasis, treatment and prognosis. However, the expression pattern of angiogenic genes, its effect on treatment and its relationship with prognosis in ESCC have not been systematically reported. We performed the first and most comprehensive multi-omics analysis of angiogenic genes in patients with ESCC and identified four angiogenic phenotypes that vary in outcome, tumor characteristics, and immune landscape. These subtypes provide not only patient outcomes but also key information that will help to identify immune blocking therapy. In addition, angiogenesis intensity score (AIS) was proposed to quantify tumor angiogenesis ability, and its accuracy as a predictor of prognosis and immunotherapy was verified by external cohort and corresponding cell lines. Our study provides clinicians with guidance for individualized immune checkpoint blocking therapy and anti-angiogenic therapy for ESCC.