Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia

Let It Grow: The Role of Growth Factors in Managing Chemotherapy-Induced Cytopenia

Chemotherapy-induced cytopenia (CIC) is characterized by neutropenia, anemia, and thrombocytopenia, which are common and serious complications in cancer treatment. These conditions affect approximately 60% of patients undergoing chemotherapy and can significantly impact quality of life, treatment continuity, and overall survival. The use of growth factors, including granulocyte colony-stimulating factors (GCSFs), erythropoietin-stimulating agents (ESAs), and thrombopoietin receptor agonists (TPO-RAs), has emerged as a promising strategy for managing CIC. However, the use of these growth factors must be approached with caution. This review provides an overview of the mechanisms, efficacy, and safety of growth factors in the management of CIC. Additionally, we discuss predictive markers for treatment response, potential risks, and highlight areas for future research.

An interactive dose optimizer based on population pharmacokinetic study to guide dosing of methotrexate in Chinese patients with osteosarcoma

PURPOSE

Osteosarcoma is a rare tumor with an incidence of 4.4 cases per million per year in adolescent. High-dose methotrexate (HD-MTX) is the standard first-line chemotherapeutic agent for osteosarcoma. However, its efficacy can vary significantly among individuals due to wide pharmacokinetic variability. Despite this, only a few population pharmacokinetics (popPK) models based on Chinese patients with osteosarcoma have been reported. Thus, this study aimed to develop a HD-MTX popPK model and an individual model-based dose optimizer for osteosarcoma therapy.

METHOD

A total of 680 MTX serum concentrations from 57 patients with osteosarcoma were measured at the end of MTX infusion and 10 h, 24 h, 48 h, and 72 h after the start of infusion. Using the first-order conditional estimation method with NONMEM, a popPK model was estimated. Goodness-of-fit plots, visual predictive checks, and bootstrap analysis were generated to evaluate the final model. A dose optimizer tool was developed based on the validated models using R Shiny. Additionally, clinical data from 12 patients with newly diagnosed osteosarcoma were collected and used as the validation set to preliminarily verify the predictive ability of the popPK model and the dose optimizer tool.

RESULTS

Body surface area (BSA) was the most significant covariate for compartment distribution. Creatinine clearance (CrCL) and co-administration of NSAIDs were introduced as predictors for central compartmental and peripheral compartmental clearance, respectively. Co-administration of NSAIDs was associated with significantly higher MTX concentrations at 72 h (p = 0.019). The dose optimizer tool exhibited a high consistency in predicting MTX AUC compared to the actual AUC (r = 0.821, p < 0.001) in the validation set.

CONCLUSION

The dose optimizer tool could be used to estimate individual PK parameters, and optimize personalized MTX therapy in particular patients.

Genetic polymorphisms and platinum-induced hematological toxicity: a systematic review

Background

Platinum-based chemotherapy bring severe hematological toxicity that can lead to dose reduction or discontinuation of therapy. Genetic variations have been reported to influence the risk and extent of hematological toxicity; however, the results are controversial and a comprehensive overview is lacking. This systematic review aimed to identify genetic biomarkers of platinum-induced hematological toxicity.

Method

Pubmed, Embase and Web of science database were systematically reviewed for studies that evaluated the association of genetic variants and platinum-related hematological toxicity in tumor patients with no prior history of chemotherapy or radiation, published from inception to the 28th of January 2022. The studies should have specific toxicity scoring system as well as defined toxicity end-point. The quality of reporting was assessed using the Strengthening the Reporting of Genetic Association Studies (STREGA) checklist. Results were summarized using narrative synthesis.

Results

83 studies were eligible with over 682 single-nucleotide polymorphisms across 110 genes. The results are inconsistent and diverse with methodological issues including insufficient sample size, population stratification, various treatment schedule and toxicity end-point, and inappropriate statistics. 11 SNPs from 10 genes (ABCB1 rs1128503, GSTP1 rs1695, GSTM1 gene deletion, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, XPC rs2228001, XPCC1 rs25487, MTHFR rs1801133, MDM2 rs2279744, TP53 rs1042522) had consistent results in more than two independent populations. Among them, GSTP1 rs1695, ERCC1 rs11615, ERCC1 rs3212986, and XRCC1 rs25487 present the most promising results.

Conclusion

Even though the results are inconsistent and several methodological concerns exist, this systematic review identified several genetic variations that deserve validation in well-defined studies with larger sample size and robust methodology.

Systematic Review Registration

https://www.crd.york.ac.uk/, identifier CRD42021234164.

Enhancer mutations modulate the severity of chemotherapy-induced myelosuppression

Non-small cell lung cancer is often diagnosed at advanced stages, and many patients are still treated with classical chemotherapy. The unselective nature of chemotherapy often results in severe myelosuppression. Previous studies showed that protein-coding mutations could not fully explain the predisposition to myelosuppression. Here, we investigate the possible role of enhancer mutations in myelosuppression susceptibility. We produced transcriptome and promoter-interaction maps (using HiCap) of three blood stem-like cell lines treated with carboplatin or gemcitabine. Taking advantage of publicly available enhancer datasets, we validated HiCap results in silico and in living cells using epigenetic CRISPR technology. We also developed a network approach for interactome analysis and detection of differentially interacting genes. Differential interaction analysis provided additional information on relevant genes and pathways for myelosuppression compared with differential gene expression analysis at the bulk level. Moreover, we showed that enhancers of differentially interacting genes are highly enriched for variants associated with differing levels of myelosuppression. Altogether, our work represents a prominent example of integrative transcriptome and gene regulatory datasets analysis for the functional annotation of noncoding mutations.

JMJD1C Regulates Megakaryopoiesis in In Vitro Models through the Actin Network

The histone demethylase JMJD1C is associated with human platelet counts. The JMJD1C knockout in zebrafish and mice leads to the ablation of megakaryocyte-erythroid lineage anemia. However, the specific expression, function, and mechanism of JMJD1C in megakaryopoiesis remain unknown. Here, we used cell line models, cord blood cells, and thrombocytopenia samples, to detect the JMJD1C expression. ShRNA of JMJD1C and a specific peptide agonist of JMJD1C, SAH-JZ3, were used to explore the JMJD1C function in the cell line models. The actin ratio in megakaryopoiesis for the JMJDC modulation was also measured. Mass spectrometry was used to identify the JMJD1C-interacting proteins. We first show the JMJD1C expression difference in the PMA-induced cell line models, the thrombopoietin (TPO)-induced megakaryocyte differentiation of the cord blood cells, and also the thrombocytopenia patients, compared to the normal controls. The ShRNA of JMJD1C and SAH-JZ3 showed different effects, which were consistent with the expression of JMJD1C in the cell line models. The effort to find the underlying mechanism of JMJD1C in megakaryopoiesis, led to the discovery that SAH-JZ3 decreases F-actin in K562 cells and increases F-actin in MEG-01 cells. We further performed mass spectrometry to identify the potential JMJD1C-interacting proteins and found that the important Ran GTPase interacts with JMJD1C. To sum up, JMJD1C probably regulates megakaryopoiesis by influencing the actin network.

JMJD1C knockdown affects myeloid cell lines proliferation, viability, and gemcitabine/carboplatin-sensitivity

OBJECTIVES

Chemotherapy-induced hematological toxicities are potentially life-threatening adverse drug reactions that vary between individuals. Recently, JMJD1C has been associated with gemcitabine/carboplatin-induced thrombocytopenia in non-small-cell lung cancer patients, making it a candidate marker for predicting the risk of toxicity. This study investigates if JMJD1C knockdown affects gemcitabine/carboplatin-sensitivity in cell lines.

METHODS

Lentiviral transduction-mediated shRNA knockdown of JMJD1C in the cell lines K562 and MEG-01 were performed using shRNA#32 and shRNA#33. The knockdown was evaluated using qPCR. Cell proliferation, viability, and gemcitabine/carboplatin-sensitivity were subsequently determined using cell counts, trypan blue, and the MTT assay.

RESULTS

ShRNA#33 resulted in JMJD1C downregulation by 56.24% in K562 and 68.10% in MEG-01. Despite incomplete knockdown, proliferation (reduction of cell numbers by 61-68%, day 7 post-transduction) and viability (reduction by 21-53%, day 7 post-transduction) were impaired in K562 and MEG-01 cells. Moreover, JMJD1C knockdown reduced the gemcitabine IC50-value for K562 cells (P < 0.01) and MEG-01 cells (P < 0.05) compared to scrambled shRNA control transduced cells.

CONCLUSIONS

Our results suggest that JMJD1C is essential for proliferation, survival, and viability of K562 and MEG-01 cells. Further, JMJD1C also potentially affects the cells gemcitabine/carboplatin-sensitivity. Although further research is required, the findings show that JMJD1C could have an influential role for gemcitabine/carboplatin-sensitivity.

A Real-World Observation of Eltrombopag and Recombinant Human Thrombopoietin (rhTPO) in Lymphoma Patients With Chemotherapy Induced Thrombocytopenia

This real-world, observational study aimed to assess and compare the clinical efficacy and safety of eltrombopag with recombinant human thrombopoietin (rhTPO) in the treatment of chemotherapy induced thrombocytopenia (CIT) in patients with lymphoma. One hundred and fifty-three patients who experienced grade 3 or 4 thrombocytopenia after chemotherapy for lymphoma were enrolled, 51 of which were treated with eltrombopag, 50 with rhTPO, and 52 patients with no drug treatment were served as the control group. The lowest platelet level and mean platelet counts at Day 5, Day 7, and Day 10 were significantly higher in both the eltrombopag group (P=.041,.003,.000,.000) and rhTPO group (P=.005,.005,.000,.000) than the control, but there was no difference between treatment with eltrombopag and rhTPO. Similarly, days required for the recovery of platelet counts to ≥50×10⁹/L and ≥75×10⁹/L were not different between the two treatment groups but significantly higher than the control group (P <.05). Rates of bleeding and platelet transfusion were all significantly reduced in patients treated with eltrombopag (P=.031,.032) or rhTPO (P=.017,.009) when compared to the control. Treatment-related adverse events (AEs) were reported in 7 (13.7%) and 6 (12.0%) patients in the eltrombopag and rhTPO groups, respectively, all being mild and transient in nature. In conclusion, both eltrombopag and rhTPO were effective and safe in the treatment of thrombocytopenia after chemotherapy for lymphoma.

Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients

Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10⁻³ for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.