Characterization of a genetic mouse model of lung cancer: a promise to identify Non-Small Cell Lung Cancer therapeutic targets and biomarkers

Personalization of Therapy in High-Grade Serous Tubo-Ovarian Cancer-The Possibility or the Necessity?

High-grade serous tubo-ovarian cancer (HGSTOC) is the most lethal tumor of the female genital tract. The foregoing therapy consists of cytoreduction followed by standard platinum/taxane chemotherapy; alternatively, for primary unresectable tumors, neo-adjuvant platinum/taxane chemotherapy followed by delayed interval cytoreduction. In patients with suboptimal surgery or advanced disease, different forms of targeted therapy have been accepted or tested in clinical trials. Studies on HGSTOC discovered its genetic and proteomic heterogeneity, epigenetic regulation, and the role of the tumor microenvironment. These findings turned attention to the fact that there are several distinct primary tumor subtypes of HGSTOC and the unique biology of primary, metastatic, and recurrent tumors may result in a differential drug response. This results in both chemo-refractoriness of some primary tumors and, what is significantly more frequent and destructive, secondary chemo-resistance of metastatic and recurrent HGSTOC tumors. Treatment possibilities for platinum-resistant disease include several chemotherapeutics with moderate activity and different targeted drugs with difficult tolerable effects. Therefore, the question appears as to why different subtypes of ovarian cancer are predominantly treated based on the same therapeutic schemes and not in an individualized way, adjusted to the biology of a specific tumor subtype and temporal moment of the disease. The paper reviews the genomic, mutational, and epigenetic signatures of HGSTOC subtypes and the tumor microenvironment. The clinical trials on personalized therapy and the overall results of a new, comprehensive approach to personalized therapy for ovarian cancer have been presented and discussed.

Pericentromeric satellite lncRNAs are induced in cancer-associated fibroblasts and regulate their functions in lung tumorigenesis

The abnormal tumor microenvironment (TME) often dictates the therapeutic response of cancer to chemo- and immuno-therapy. Aberrant expression of pericentromeric satellite repeats has been reported for epithelial cancers, including lung cancer. However, the transcription of tandemly repetitive elements in stromal cells of the TME has been unappreciated, limiting the optimal use of satellite transcripts as biomarkers or anti-cancer targets. We found that transcription of pericentromeric satellite DNA (satDNA) in mouse and human lung adenocarcinoma was observed in cancer-associated fibroblasts (CAFs). In vivo, lung fibroblasts expressed pericentromeric satellite repeats HS2/HS3 specifically in tumors. In vitro, transcription of satDNA was induced in lung fibroblasts in response to TGFβ, IL1α, matrix stiffness, direct contact with tumor cells and treatment with chemotherapeutic drugs. Single-cell transcriptome analysis of human lung adenocarcinoma confirmed that CAFs were the cell type with the highest number of satellite transcripts. Human HS2/HS3 pericentromeric transcripts were detected in the nucleus, cytoplasm, extracellularly and co-localized with extracellular vesicles in situ in human biopsies and activated fibroblasts in vitro. The transcripts were transmitted into recipient cells and entered their nuclei. Knock-down of satellite transcripts in human lung fibroblasts attenuated cellular senescence and blocked the formation of an inflammatory CAFs phenotype which resulted in the inhibition of their pro-tumorigenic functions. In sum, our data suggest that satellite long non-coding (lnc) RNAs are induced in CAFs, regulate expression of inflammatory genes and can be secreted from the cells, which potentially might present a new element of cell-cell communication in the TME.

Identification of a six-gene prognostic signature for bladder cancer associated macrophage

As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers.

Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile

(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.

Identification of a novel subpopulation of Caspase-4 positive non-small cell lung Cancer patients

BACKGROUND

Therapy/prognosis of Non-Small Cell Lung Cancer (NSCLC) patients are strongly related to gene alteration/s or protein expression. However, more than 50% of NSCLC patients are negative to key drugable biomarkers.

METHODS

We used human samples of NSCLC and mouse models of lung adenocarcinoma.

RESULTS

We showed that caspase-4 was highly present in the tumor mass compared to non-cancerous human tissues. Interestingly, the orthologue murine caspase-11 promoted lung carcinogenesis in mice. Carcinogen-exposed caspase-11 knockout mice had lower tumor lesions than wild type mice, due to the relevance of caspase-11 in the structural lung cell as demonstrated by bone marrow transplantation and adoptive transfer experiments. Similarly to what observed in mice, caspase-4 was correlated to the stage of lung cancer in humans in that it induced cell proliferation in a K-Ras, c-MyC and IL-1α dependent manner. Caspase-4 positive adenocarcinoma (79.3%) and squamous carcinoma (88.2%) patients had lower median survival than patients who had lower levels of caspase-4. Moreover, PD-L1 expression and gene mutation (i.e. EGFR) were not correlated to caspase-4 expression. Instead, NSCLC patients who had K-Ras or c-MyC gene alteration were positively correlated to higher levels of caspase-4 and lower survival rate.

CONCLUSIONS

We identified a subgroup of NSCLC patients as caspase-4 positive among which double and triple positive caspase-4, K-Ras and/or c-MyC patients which prognosis was poor. Because K-Ras and c-MyC are still undrugable, the identification of caspase-4 as a novel oncoprotein could introduce novelty in the clinical yet unmet needs for NSCLC patients.

Immunization against ROS1 by DNA Electroporation Impairs K-Ras-Driven Lung Adenocarcinomas ​

Non-small cell lung cancer (NSCLC) is still the leading cause of cancer death worldwide. Despite the introduction of tyrosine kinase inhibitors and immunotherapeutic approaches, there is still an urgent need for novel strategies to improve patient survival. ROS1, a tyrosine kinase receptor endowed with oncoantigen features, is activated by chromosomal rearrangement or overexpression in NSCLC and in several tumor histotypes. In this work, we have exploited transgenic mice harboring the activated K-Ras oncogene (K-Ras^G12D) that spontaneously develop metastatic NSCLC as a preclinical model to test the efficacy of ROS1 immune targeting. Indeed, qPCR and immunohistochemical analyses revealed ROS1 overexpression in the autochthonous primary tumors and extrathoracic metastases developed by K-Ras^G12D mice and in a derived transplantable cell line. As proof of concept, we have evaluated the effects of the intramuscular electroporation (electrovaccination) of plasmids coding for mouse- and human-ROS1 on the progression of these NSCLC models. A significant increase in survival was observed in ROS1-electrovaccinated mice challenged with the transplantable cell line. It is worth noting that tumors were completely rejected, and immune memory was achieved, albeit only in a few mice. Most importantly, ROS1 electrovaccination was also found to be effective in slowing the development of autochthonous NSCLC in K-Ras^G12D mice.

Identification of Secreted Phosphoprotein 1 (SPP1) as a Prognostic Factor in Lower-Grade Gliomas

OBJECTIVE

Secreted phosphoprotein 1 (SPP1) is an important extracellular glycoprotein that is associated with immune regulation, tumorigenesis, and cell signaling. However, the prognostic value of SPP1 in patients with glioma has not yet been clarified, especially in lower-grade gliomas. The objective of this study is to evaluate the prognostic merit of SPP1 in lower-grade gliomas.

METHODS

The messenger RNA (mRNA) expression of SPP1 in about 1000 cancer cell lines was explored by using the data from the Cancer Cell Line Encyclopedia database. The Oncomine database was mined to evaluate the mRNA expression of SPP1 in lower-grade glioma, glioblastoma, and normal brain tissues. The correlation between SPP1 mRNA expression and overall survival of patients with glioma from The Cancer Genome Atlas database was analyzed.

RESULTS

SPP1 mRNA expression of glioma was ranked as the eighth highest of all cancer cell lines in the Cancer Cell Line Encyclopedia database. The data from the Oncomine database suggested that SPP1 expression was significantly high in glioblastoma compared with normal brain tissues but was not significantly high in lower-grade glioma compared with normal brain tissue. Analysis of the RNA-Seq data from The Cancer Genome Atlas database showed that the increased SPP1 mRNA expression in lower-grade glioma was significantly associated with poor survival outcomes in patients with lower-grade glioma. Multivariate Cox regression analysis showed that SPP1 might be considered as an independent prognostic factor in lower-grade gliomas.

CONCLUSIONS

The present study showed that SPP1 overexpression is related to worse overall survival in patients with lower-grade glioma. Moreover, SPP1 could be considered as an independent factor in lower-grade gliomas.

Genome-wide analysis reveals alcohol dehydrogenase 1C and secreted phosphoprotein 1 for prognostic biomarkers in lung adenocarcinoma

To seek out novel promising biomarkers for predicting lung adenocarcinoma (LUAD) prognosis, we conducted this study. First, 279 upregulated and 37 downregulated differentially expressed genes were obtained from LUAD and para-carcinoma tissues by the Affymetrix GeneChip Human Transcriptome Array. Then, we randomly classified samples of LUAD data set GSE31210 as training and testing sets in a 1:1 ratio. Alcohol dehydrogenase 1C (ADH1C) and secreted phosphoprotein 1 (SPP1) were finally identified correlating with the LUAD survival through least absolute shrinkage and selection operator penalized Cox proportion hazards regression model, and applied to build a 2-gene signature related to prognosis in training set. Univariate and multivariable survival analyses suggested that overall survival (OS) and relapse-free survival (RFS) in the 2-gene signature low-risk group were better than the high-risk group. Kaplan-Meier curves proved that elevated ADH1C expression and reduced SPP1 expression were related to better OS and RFS. Besides, the SPP1 expressed higher in LUAD than para-carcinoma tissues using quantitative reverse transcription polymerase chain reaction assay. Finally, the association between the two genes and clinicopathological parameters in 80 LUAD were analyzed, it is suggested that SPP1 was relevant to epidermal growth factor receptor mutation. These findings indicated that ADH1C and SPP1 might be novel promising biomarkers for predicting LUAD prognosis.

Crizotinib presented with promising efficacy but for concomitant mutation in next-generation sequencing-identified ROS1-rearranged non-small-cell lung cancer

Introduction

Data of standard tyrosine kinase inhibitor (TKI) treatment outcome in next-generation sequencing (NGS)-identified ROS1-rearranged non-small-cell lung cancer (NSCLC) were rare. Thus, it is practical and necessary to evaluate the efficacy and influential factors of crizotinib in real-world practice.

Patients and methods

A total of 1,466 NSCLC patients with positive targeted NGS test results from September 2015 to January 2018 were enrolled in this real-world retrospective study. Twenty-two patients had ROS1 rearrangement detected by NGS. The efficacy and safety of crizotinib were evaluated. Subgroups of concomitant mutations, brain metastasis, and fusion variants were also analyzed.

Results

Among all the patients, the occurrence rate of ROS1 rearrangement was 1.5% (22 of 1,466). Ten ROS1 fusion partners were detected, and the most common variant was CD74, which accounted for 50% (11 of 22). Five patients were found to carry dual ROS1 fusion partners, and 23% (5 of 22) of patients were detected with concomitant mutations, including TP53&PIK3CA&mTOR mutation, TP53&CDKN2A mutation, TP53&BRCA2 mutation, ALK missense mutation (p.R311H), and MET amplification. Among 22 patients with ROS1-rearranged NSCLC, 20 patients were diagnosed at stage IV, and 19 patients received crizotinib treatment. The average follow-up period was 16 months. The overall response rate (ORR) of crizotinib in unselected crizotinib-treated patients was 89%, and the median progression-free survival time (mPFS) was 13.6 months. It was shown that NSCLC patients with exclusive ROS1 rearrangement had a longer PFS than those carrying concomitant mutations (15.5 vs 8.5 months, P=0.0213). There were no newly occurring intolerant adverse events in this study.

Conclusion

Crizotinib is highly effective in NGS-identified ROS1-rearranged advanced NSCLC in real-word clinical practice, and the data are consistent with previous clinical trials applying fluorescence in situ hybridization/real-time PCR for ROS1 companion diagnosis. Concomitant mutations may not be rare and may deteriorate the PFS of crizotinib in patients with ROS1-rearranged NSCLC.

A common CD55 rs2564978 variant is associated with the susceptibility of non-small cell lung cancer

CD55, as one of key membrane-bound complement-regulatory proteins (mCRPs), is crucial for the progression of various cancers. This study aims to investigate the role of CD55 variants in the development of non-small cell lung cancer (NSCLC). A case-control study, including 706 lung cancer cases and 706 health controls, was conducted in a Chinese population. The odds ratio (OR) and 95% confidence interval (95% CI) were estimated by unconditional logistic regression. We found that significantly higher lung cancer risk was linked with CD55 rs2564978 CC genotype (OR = 1.52, 95% CI = 1.11−2.07) or CT genotypes (OR = 1.34, 95% CI = 1.05−1.71), compared to the TT genotype. Stratified analysis showed that rs2564978 CC was associated with NSCLC risk among males (OR = 1.69, 95% CI = 1.14−2.49) and older subjects (OR = 1.75, 95% CI = 1.08−2.82). When stratified by smoking status, the risk effect of rs2564978 CC was more evident among smokers (OR = 2.01, 95% CI = 1.18−3.43) than non-smokers (OR = 1.30, 95% CI = 0.88−1.90). We also conducted the stratified analysis by NSCLC histological types and found that CD55 rs2564978 CC increased the risk of adenocarcinoma with OR (95% CI) of 1.35 (1.01−1.80). The reporter gene expression driven by rs2564978T-containing CD55 promoter was respectively 1.48-fold, 1.96-fold and 1.93-fold higher than those driven by the rs2564978C-containing CD55 promoter in A549, NCI-H2030 and NCI-H23 cells (P = 0.045, 0.010 and < 0.001). These findings indicate that CD55 rs2564978 polymorphism may contribute to an increased risk of NSCLC in Chinese population.

GRHL2 suppresses tumor metastasis via regulation of transcriptional activity of RhoG in non-small cell lung cancer

The transcription factor, Grainyhead-like 2 (GRHL2), is involved in wound healing, epidermal integrity, and epithelial-to-mesenchymal transition (EMT) in various biological processes; however, the biological function of GRHL2 in non-small cell lung cancer (NSCLC) is unknown. In the current study, we investigated the effect of GRHL2 on cell growth and migration in NSCLC cell lines and clinical tissues. Immunohistochemical analysis of clinical NSCLC specimens revealed that patients with high GRHL2 expression were associated with poor prognosis compared to patients with low GRHL2 expression. GRHL2 overexpression promoted cell growth and colony formation, and simultaneously suppressed cell migration in NSCLC cells. Furthermore, GRHL2 decreased the transcriptional activity of RhoG by directly binding to the RhoG promoter region. These findings confirm that GRHL2 plays an important role in regulating cell proliferation and migration in NSCLC.

Integrated analysis of differential expression and alternative splicing of non-small cell lung cancer based on RNA sequencing

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with high morbidity and mortality rates. Numerous diagnosis and treatment methods have been proposed, and the prognosis of NSCLC has improved to a certain extent. However, the mechanisms of NSCLC remain largely unknown, and additional studies are required. In the present study, the RNA sequencing dataset of NSCLC was downloaded from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). The clean reads obtained from the raw data were mapped to the University of California Santa Cruz human genome (hg19), based on TopHat, and were assembled into transcripts via Cufflink. The differential expression (DE) and differential alternative splicing (DAS) genes were screened out through Cuffdiff and rMATS, respectively. The significantly enriched gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes pathways were obtained through the Database of Annotation, Visualization and Integrated Discovery (DAVID). Different numbers of DE and DAS genes were identified in different types of NSCLC samples, but a number of common functions and pathways were obtained, including biological processes associated with abnormal immune and cell activity. GO terms and pathways associated with substance metabolism, including the insulin signaling pathway and oxidative phosphorylation, were enriched in DAS genes rather than DE genes. Integrated analysis of differential expression and alternative splicing may be helpful in understanding the mechanisms of NSCLC, in addition to its early diagnosis and treatment.

Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer

Purpose

We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients.

Materials and Methods

We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedOvarianData database.

Results

We identified 21 mRNAs, and seven methylated DNAs from primary EOC tissues that predicted lymphatic invasion and created prognostic models. The classifier predicted lymphatic invasion well, which was validated by logistic regression, LDA, and SVM algorithm (C-index of 0.90, 0.71, and 0.74 for mRNA and C-index of 0.64, 0.68, and 0.69 for DNA methylation). Using RSF model, incorporating molecular data with clinical variables improved prediction of progression-free survival compared with using only clinical variables (p < 0.001 and p=0.008). Similarly, PDS enabled us to classify patients into high-risk and low-risk group, which resulted in survival difference in mRNA profiles (log-rank p-value=0.011). In external validation, gene signature was well correlated with prediction of lymphatic invasion and patients’ survival.

Conclusion

Molecular signature model predicting lymphatic invasion was well performed and also associated with survival of EOC patients.

Immunotargeting of Antigen xCT Attenuates Stem-like Cell Behavior and Metastatic Progression in Breast Cancer

Resistance to therapy and lack of curative treatments for metastatic breast cancer suggest that current therapies may be missing the subpopulation of chemoresistant and radioresistant cancer stem cells (CSC). The ultimate success of any treatment may well rest on CSC eradication, but specific anti-CSC therapies are still limited. A comparison of the transcriptional profiles of murine Her2(+) breast tumor TUBO cells and their derived CSC-enriched tumorspheres has identified xCT, the functional subunit of the cystine/glutamate antiporter system xc(-), as a surface protein that is upregulated specifically in tumorspheres. We validated this finding by cytofluorimetric analysis and immunofluorescence in TUBO-derived tumorspheres and in a panel of mouse and human triple negative breast cancer cell-derived tumorspheres. We further show that downregulation of xCT impaired tumorsphere generation and altered CSC intracellular redox balance in vitro, suggesting that xCT plays a functional role in CSC biology. DNA vaccination based immunotargeting of xCT in mice challenged with syngeneic tumorsphere-derived cells delayed established subcutaneous tumor growth and strongly impaired pulmonary metastasis formation by generating anti-xCT antibodies able to alter CSC self-renewal and redox balance. Finally, anti-xCT vaccination increased CSC chemosensitivity to doxorubicin in vivo, indicating that xCT immunotargeting may be an effective adjuvant to chemotherapy.

Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge

Microarrays can provide large amounts of data for genetic relative expression in illnesses of interest such as cancer in short time. These data, however, are stored and often times abandoned when new experimental technologies arrive. This work reexamines lung cancer microarray data with a novel multiple criteria optimization‐based strategy aiming to detect highly differentially expressed genes. This strategy does not require any adjustment of parameters by the user and is capable to handle multiple and incommensurate units across microarrays. In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer. The list of genes is provided with a discussion of their role in cancer, as well as the possible research directions for each of them.

Expression pattern of FGFR2, Grb2 and Plcγ1 acts as a novel prognostic marker of recurrence recurrence-free survival in lung adenocarcinoma

Lung adenocarcinoma is characterized by complex biology involving alterations at the genomic and protein expression levels. FGFR2 mutation and/or amplification are key drivers of disease progression and drug resistance in lung adenocarcinoma patients. These genetic alterations drive oncogenic downstream signalling due to the deregulated activity of the receptor. We have previously reported that wild type FGFR2 provides a binding site for which two proteins, Grb2 and Plcγ1, compete in a concentration-dependent manner. Metastasis and invasion ensue when Plcγ1 prevails on the receptor giving rise to oncogenic outcome in the absence of gene mutation/deletion. The effect of this signalling mechanism on FGFR2-driven lung adenocarcinoma has not previously been considered. In this study we show that fluctuation in the combinatorial expression levels of FGFR2, Grb2 and Plcγ1 modulates cell invasive properties, tumor formation and is linked to recurrence-free survival in 150 lung adenocarcinoma patients. High levels of expression of FGFR2 and Plcγ1 in a low background of Grb2 significantly correlates with poor prognosis. On the other hand, low levels of expression of FGFR2 and Plcγ1 in a high background of Grb2 correlates with favourable prognosis. This study defines the expression pattern of FGFR2, Plcγ1 and Grb2 as a novel prognostic marker in human lung adenocarcinoma. Thus, consideration of the Grb2 and Plcγ1-mediated mechanism of FGFR2 regulation will enhance the therapeutic targeting of aberrant FGFR2 activity to provide the much-needed improvement to the treatment regimen of this high mortality disease.

Novel Drug Targets for Food-Borne Pathogen Campylobacter jejuni: An Integrated Subtractive Genomics and Comparative Metabolic Pathway Study

Campylobacters are a major global health burden and a cause of food-borne diarrheal illness and economic loss worldwide. In developing countries, Campylobacter infections are frequent in children under age two and may be associated with mortality. In developed countries, they are a common cause of bacterial diarrhea in early adulthood. In the United States, antibiotic resistance against Campylobacter is notably increased from 13% in 1997 to nearly 25% in 2011. Novel drug targets are urgently needed but remain a daunting task to accomplish. We suggest that omics-guided drug discovery is timely and worth considering in this context. The present study employed an integrated subtractive genomics and comparative metabolic pathway analysis approach. We identified 16 unique pathways from Campylobacter when compared against H. sapiens with 326 non-redundant proteins; 115 of these were found to be essential in the Database of Essential Genes. Sixty-six proteins among these were non-homologous to the human proteome. Six membrane proteins, of which four are transporters, have been proposed as potential vaccine candidates. Screening of 66 essential non-homologous proteins against DrugBank resulted in identification of 34 proteins with drug-ability potential, many of which play critical roles in bacterial growth and survival. Out of these, eight proteins had approved drug targets available in DrugBank, the majority serving crucial roles in cell wall synthesis and energy metabolism and therefore having the potential to be utilized as drug targets. We conclude by underscoring that screening against these proteins with inhibitors may aid in future discovery of novel therapeutics against campylobacteriosis in ways that will be pathogen specific, and thus have minimal toxic effect on host. Omics-guided drug discovery and bioinformatics analyses offer the broad potential for veritable advances in global health relevant novel therapeutics.