Clinical Updates for Colon Cancer Care in 2022

Fabregas, Jesus C.; Ramnaraign, Brian Hemendra; George, Thomas J.

doi:10.1016/j.clcc.2022.05.006

Cited by 78 publications

(42 citation statements)

References 47 publications

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“…In spite of many advances in early diagnosis and clinical cure for COAD, the morbidity and mortality rates of the disease remain high 14–16 . Mitochondria are the main site of aerobic respiration and the energy factory of cells.…”

Section: Discussionmentioning

confidence: 99%

“…In spite of many advances in early diagnosis and clinical cure for COAD, the morbidity and mortality rates of the disease remain high. [14][15][16] Mitochondria are the main site of aerobic respiration and the energy factory of cells. Warburg 17,18 first observed the unusual property of cancer cells to ferment glucose into lactate under aerobic conditions, proposing that mitochondrial respiratory defects are a feasible basis for aerobic glycolysis and cancer.…”

Section: Discussionmentioning

confidence: 99%

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Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance

Zhang

Liang

Zhou

et al. 2023

J of Molecular Recognition

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Mitochondria are the main sites of oxidative metabolism and energy release of sugars, fats and amino acids in the body. According to studies, malignant tumor occurrence and development have been linked to abnormal mitochondrial energy metabolism (MEM). However, the feasible role of abnormal MEM in colon adenocarcinoma (COAD) is poorly understood. In this work, we obtained COAD patient data from The Cancer Genome Atlas (TCGA) as the training set, and GSE103479 from Gene Expression Omnibus (GEO) as the validation set. Combined with the mitochondrial energy metabolic pathway (MEMP)-related genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a risk prognostic model was constructed by utilizing Cox regression analysis to identify 6 feature genes (CYP4A11, PGM2, PKLR, PPARGC1A, CPT2 and ACAT2) that were significantly associated with MEMP in COAD. By stratifying the samples based on riskscore, two distinct groups, namely the high-and low-risk groups, were identified. The model demonstrated accurate assessment of the prognosis risk in COAD patients and exhibited independent prognostic capability, as evidenced by the survival curve and receiver operating characteristic (ROC) curve analysis. A nomogram was plotted based on clinical information and riskscore. We proved it could predict the survival time of COAD patients effectively combined with the calibration curve of risk prediction. Subsequently, based on the immune evaluation and mutation frequency analysis performed on COAD patients, patients in high-risk group had observably higher immune scores, immune activity and PDCD1 expression level than low-risk group. In general, the prognostic model developed using MEMP-related genes served as a valuable biomarker for forecasting the prognosis of COAD patients, which offered a reference for the prognosis evaluation and clinical cure of COAD patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance

Zhang

Liang

Zhou

et al. 2023

J of Molecular Recognition

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“…Currently, the standard of care for colorectal cancer patients is a combination of surgery and adjuvant chemotherapy [ 96 ]. One of the main focuses of targeted treatments in colorectal cancer is EGFR, which upon homo- or hetero-dimerization with another RTK to activate downstream signaling pathways.…”

Section: Incidence Of Her3 Mutations In Human Cancersmentioning

confidence: 99%

HER3 Alterations in Cancer and Potential Clinical Implications

Kilroy

Park

Feroz

et al. 2022

Cancers

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In recent years, the third member of the HER family, kinase impaired HER3, has become a target of interest in cancer as there is accumulating evidence that HER3 plays a role in tumor growth and progression. This review focuses on HER3 activation in bladder, breast, colorectal, and lung cancer disease progression. HER3 mutations occur at a rate up to ~10% of tumors dependent on the tumor type. With patient tumors routinely sequenced for gene alterations in recent years, we have focused on HER3 mutations in bladder, breast, colon, and lung cancers particularly in response to targeted therapies and the potential to become a resistance mechanism. There are currently several HER3 targeting drugs in the pipeline, possibly improving outcomes for cancer patients with tumors containing HER3 activation and/or alterations.

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“…Colon cancer is among the most serious cancers worldwide and is genetically complex[ 1 , 2 ]. According to the World Health Organization (WHO), over 940000 cases are reported worldwide, and almost 500000 people die annually of colon cancer[ 3 ]. As with other solid cancers, colon cancer is infested with various types of immune cells.…”

Section: Introductionmentioning

confidence: 99%

Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer

Huang¹,

Bao²,

Huang³

et al. 2023

World J Gastrointest Oncol

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BACKGROUND Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease. AIM To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients. The main purpose was to assess whether reasonable induction of these biomarkers reduces mortality among patients with colon cancers. METHOD Data obtained from The Cancer Genome Atlas and Gene Expression Omnibus and the Genotype-Tissue Expression were used in differential analysis to explore differential expression genes associated with cuproptosis and immune activation. The least absolute shrinkage and selection operator and Cox regression algorithm was applied to build a cuproptosis- and immune-related combination model, and the model was utilized for principal component analysis and survival analysis to observe the survival and prognosis of the patients. A series of statistically meaningful transcriptional analysis results demonstrated an intrinsic relationship between cuproptosis and the micro-environment of colon cancer. RESULTS Once prognostic characteristics were obtained, the CDKN2A and DLAT genes related to cuproptosis were strongly linked to colon cancer: The first was a risk factor, whereas the second was a protective factor. The finding of the validation analysis showed that the comprehensive model associated with cuproptosis and immunity was statistically significant. Within the component expressions, the expressions of HSPA1A, CDKN2A, and UCN3 differed markedly. Transcription analysis primarily reflects the differential activation of related immune cells and pathways. Furthermore, genes linked to immune checkpoint inhibitors were expressed differently between the subgroups, which may reveal the mechanism of worse prognosis and the different sensitivities of chemotherapy. CONCLUSION The prognosis of the high-risk group evaluated in the combined model was poorer, and cuproptosis was highly correlated with the prognosis of colon cancer. It is possible that we may be able to improve patients’ prognosis by regulating the gene expression to intervene the risk score.

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Clinical Updates for Colon Cancer Care in 2022

Cited by 78 publications

References 47 publications

Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance

Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance

HER3 Alterations in Cancer and Potential Clinical Implications

Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer

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