Identification of targeted therapy options for gastric adenocarcinoma by comprehensive analysis of genomic data

Advances in targeted therapy for human epidermal growth factor receptor 2 positive in advanced gastric cancer

Emerging therapeutic methods represented by targeted therapy are effective supplements to traditional first-line chemoradiotherapy resistance. Human epidermal growth factor receptor 2 (HER2) is one of the most important targets in targeted therapy for gastric cancer. Trastuzumab combined with chemotherapy has been used as the first-line treatment for advanced gastric cancer. The safety and efficacy of pertuzumab and margetuximab in the treatment of gastric cancer have been verified. However, monoclonal antibodies, due to their large molecular weight, inability to penetrate the blood-brain barrier, and drug resistance, lead to decreased therapeutic efficacy, so it is necessary to explore the efficacy of other HER2-targeting therapies in gastric cancer. Small-molecule tyrosine kinase inhibitors, such as lapatinib and pyrrotinib, have the advantages of small molecular weight, penetrating the blood-brain barrier and high oral bioavailability, and are expected to become the drugs of choice for perioperative treatment and neoadjuvant therapy of gastric cancer after validation by large-scale clinical trials in the future. Antibo-drug conjugate, such as T-DM1 and T-DXd, can overcome the resistance of monoclonal antibodies despite their different mechanisms of tumor killing, and are a supplement for the treatment of patients who have failed the treatment of monoclonal antibodies such as trastuzumab. Therefore, after more detailed stratification of gastric cancer patients, various gastric cancer drugs targeting HER2 are expected to play a more significant role.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

Upregulation of PIK3IP1 monitors the anti-cancer activity of PI3Kα inhibitors in gastric cancer cells

Gastric cancer remains one of the most malignant cancers in the world. The target-based drugs approved by FDA for gastric cancer treatment include only three targets and benefit a small portion of gastric cancer patients. PIK3CA, a confirmed oncogene, mutates in 7-25% gastric cancer patients. PI3Kα inhibitor BYL719 has been approved for treating specific breast cancer. However, there is no comprehensive study about PI3Kα inhibitor in gastric cancer. In this study, we found pharmacological inhibition or knockdown of PI3Kα effectively inhibited the proliferation of partial gastric cancer cells. Then, we systematically explored the potential biomarkers for predicting or monitoring treatment response according to previous reports and found that basal expression of several receptor tyrosine kinases were related with the sensitivity of gastric cancer cells to BYL719. Next, RNA-seq technique was utilized and showed that BYL719 inhibited Myc targets V2 gene set in sensitive gastric cancer cells, and western blotting further verified that c-Myc was only inhibited in sensitive gastric cancer cells. More importantly, we firstly found BYL719 significantly elevated the expression of PIK3IP1 in sensitive gastric cancer cells, which was also observed in NCI-N87 cell derived xenograft mice models. Meanwhile, knockdown of PIK3IP1 partially rescued the cell growth inhibited by BYL719 in sensitive gastric cancer cells, suggesting the important role of PIK3IP1 in the antitumor activity of BYL719. In conclusion, our study provides biological evidence that PI3Kα is a promising target in specific gastric cancer and the elevation of PIK3IP1 could supply as a biomarker that monitoring treatment response.

Targeted Therapy for Adrenocortical Carcinoma: A Genomic-Based Search for Available and Emerging Options

In rare diseases such as adrenocortical carcinoma (ACC), in silico analysis can help select promising therapy options. We screened all drugs approved by the FDA and those in current clinical studies to identify drugs that target genomic alterations, also known to be present in patients with ACC. We identified FDA-approved drugs in the My Cancer Genome and National Cancer Institute databases and identified genetic alterations that could predict drug response. In total, 155 FDA-approved drugs and 905 drugs in clinical trials were identified and linked to 375 genes of 89 TCGA patients. The most frequent potentially targetable genetic alterations included TP53 (20%), BRD9 (13%), TERT (13%), CTNNB1 (13%), CDK4 (7%), FLT4 (7%), and MDM2 (7%). We identified TP53-modulating drugs to be possibly effective in 20-26% of patients, followed by the Wnt signaling pathway inhibitors (15%), Telomelysin and INO5401 (13%), FHD-609 (13%), etc. According to our data, 67% of ACC patients exhibited genomic alterations that might be targeted by FDA-approved drugs or drugs being tested in current clinical trials. Although there are not many current therapy options directly targeting reported ACC alterations, this study identifies emerging options that could be tested in clinical trials.

Anaplastic thyroid cancer: genome-based search for new targeted therapy options

OBJECTIVE

Anaplastic thyroid cancer (ATC) is one of the most lethal human cancers with meager treatment options. We aimed to identify the targeted drugs already approved by the Food and Drug Administration (FDA) for solid cancer in general, which could be effective in ATC.

DESIGN

Database mining.

METHODS

FDA-approved drugs for targeted therapy were identified by screening the databases of MyCancerGenome and the National Cancer Institute. Drugs were linked to the target genes by querying Drugbank. Subsequently, MyCancerGenome, CIViC, TARGET and OncoKB were mined for genetic alterations which are predicted to lead to drug sensitivity or resistance. We searched the Cancer Genome Atlas database (TCGA) for patients with ATC and probed their sequencing data for genetic alterations which predict a drug response.

RESULTS

In the study,155 FDA-approved drugs with 136 potentially targetable genes were identified. Seventeen (52%) of 33 patients found in TCGA had at least one genetic alteration in targetable genes. The point mutation BRAF V600E was seen in 45% of patients. PIK3CA occurred in 18% of cases. Amplifications of ALK and SRC were detected in 3% of cases, respectively. Fifteen percent of the patients displayed a co-mutation of BRAF and PIK3CA. Besides BRAF-inhibitors, the PIK3CA-inhibitor copanlisib showed a genetically predicted response. The 146 (94%) remaining drugs showed no or low (under 4% cases) genetically predicted drug response.

CONCLUSIONS

While ATC carrying BRAF mutations can benefit from BRAF inhibitors and this effect might be enhanced by a combined strategy including PIK3CA inhibitors in some of the patients, alterations in BRAFWT ATC are not directly targeted by currently FDA-approved options.

Multi-Omics Profiling Suggesting Intratumoral Mast Cells as Predictive Index of Breast Cancer Lung Metastasis

Breast cancer lung metastasis has a high mortality rate and lacks effective treatments, for the factors that determine breast cancer lung metastasis are not yet well understood. In this study, data from 1067 primary tumors in four public datasets revealed the distinct microenvironments and immune composition among patients with or without lung metastasis. We used multi-omics data of the TCGA cohort to emphasize the following characteristics that may lead to lung metastasis: more aggressive tumor malignant behaviors, severer genomic instability, higher immunogenicity but showed generalized inhibition of effector functions of immune cells. Furthermore, we found that mast cell fraction can be used as an index for individual lung metastasis status prediction and verified in the 20 human breast cancer samples. The lower mast cell infiltrations correlated with tumors that were more malignant and prone to have lung metastasis. This study is the first comprehensive analysis of the molecular and cellular characteristics and mutation profiles of breast cancer lung metastasis, which may be applicable for prognostic prediction and aid in choosing appropriate medical examinations and therapeutic regimens.

Targeted Therapy of Papillary Thyroid Cancer: A Comprehensive Genomic Analysis

Background

A limited number of targeted therapy options exist for papillary thyroid cancer (PTC) to date. Based on genetic alterations reported by the "The Cancer Genome Atlas (TCGA)", we explored whether PTC shows alterations that may be targetable by drugs approved by the FDA for other solid cancers.

Methods

Databases of the National Cancer Institute and MyCancerGenome were screened to identify FDA-approved drugs for targeted therapy. Target genes were identified using Drugbank. Genetic alterations were classified into conferring drug sensitivity or resistance using MyCancerGenome, CiViC, TARGET, and OncoKB. Genomic data for PTC were extracted from TCGA and mined for alterations predicting drug response.

Results

A total of 129 FDA-approved drugs with 128 targetable genes were identified. One hundred ninety-six (70%) of 282 classic, 21 (25%) of 84 follicular, and all 30 tall-cell variant PTCs harbored druggable alterations: 259 occurred in 29, 39 in 19, and 31 in 2 targetable genes, respectively. The BRAF V600 mutation was seen in 68% of classic, 16% of follicular variant, and 93% of tall-cell variant PTCs. The RET gene fusion was seen in 8% of classic PTCs, NTRK1 and 3 gene fusions in 3%, and other alterations in <2% of classic variant PTCs. Ninety-nine of 128 (77%) FDA-approved targetable genes did not show any genetic alteration in PTC. Beside selective and non-selective BRAF-inhibitors, no other FDA-approved drug showed any frequent predicted drug sensitivity (<10%).

Conclusion

Treatment strategies need to focus on resistance mechanisms to BRAF inhibition and on genetic alteration-independent alternatives rather than on current targeted drugs.