Predictive Value of Ex Vivo Chemosensitivity Assays for Individualized Cancer Chemotherapy: A Meta-Analysis

Exhaustive in vitro evaluation of the 9-drug cocktail CUSP9 for treatment of glioblastoma

The CUSP9 protocol is a polypharmaceutical strategy aiming at addressing the complexity of glioblastoma by targeting multiple pathways. Although the rationale for this 9-drug cocktail is well-supported by theoretical and in vitro data, its effectiveness compared to its 511 possible subsets has not been comprehensively evaluated. Such an analysis could reveal if fewer drugs could achieve similar or better outcomes. We conducted an exhaustive in vitro evaluation of the CUSP9 protocol using COMBImageDL, our specialized framework for testing higher-order drug combinations. This study assessed all 511 subsets of the CUSP9v3 protocol, in combination with temozolomide, on two clonal cultures of glioma-initiating cells derived from patient samples. The drugs were used at fixed, clinically relevant concentrations, and the experiment was performed in quadruplicate with endpoint cell viability and live-cell imaging readouts. Our results showed that several lower-order drug combinations produced effects equivalent to the full CUSP9 cocktail, indicating potential for simplified regimens in personalized therapy. Further validation through in vivo and precision medicine testing is required. Notably, a subset of four drugs (auranofin, disulfiram, itraconazole, sertraline) was particularly effective, reducing cell growth, altering cell morphology, increasing apoptotic-like cells within 4-28 h, and significantly decreasing cell viability after 68 h compared to untreated cells. This study underscores the importance and feasibility of comprehensive in vitro evaluations of complex drug combinations on patient-derived tumor cells, serving as a critical step toward (pre-)clinical development.

Multimodal machine learning models identify chemotherapy drugs with prospective clinical efficacy in dogs with relapsed B-cell lymphoma

Dogs with B-cell lymphoma typically respond well to first-line CHOP-based chemotherapy, but there is no standard of care for relapsed patients. To help veterinary oncologists select effective drugs for dogs with lymphoid malignancies such as B-cell lymphoma, we have developed multimodal machine learning models that integrate data from multiple tumor profiling modalities and predict the likelihood of a positive clinical response for 10 commonly used chemotherapy drugs. Here we report on clinical outcomes that occurred after oncologists received a prediction report generated by our models. Remarkably, we found that dogs that received drugs predicted to be effective by the models experienced better clinical outcomes by every metric we analyzed (overall response rate, complete response rate, duration of complete response, patient survival times) relative to other dogs in the study and relative to historical controls.

Circulating tumour cell gene expression and chemosensitivity analyses: predictive accuracy for response to multidisciplinary treatment of patients with unresectable refractory recurrent rectal cancer or unresectable refractory colorectal cancer liver metastases

Background

Patients with unresectable recurrent rectal cancer (RRC) or colorectal cancer (CRC) with liver metastases, refractory to at least two lines of traditional systemic therapy, may receive third line intraarterial chemotherapy (IC) and targeted therapy (TT) using drugs selected by chemosensitivity and tumor gene expression analyses of liquid biopsy-derived circulating tumor cells (CTCs).

Methods

In this retrospective study, 36 patients with refractory unresectable RRC or refractory unresectable CRC liver metastases were submitted for IC and TT with agents selected by precision oncotherapy chemosensitivity assays performed on liquid biopsy-derived CTCs, transiently cultured in vitro, and by tumor gene expression in the same CTC population, as a ratio to tumor gene expression in peripheral mononuclear blood cells (PMBCs) from the same individual. The endpoint was to evaluate the predictive accuracy of a specific liquid biopsy precision oncotherapy CTC purification and in vitro culture methodology for a positive RECIST 1.1 response to the therapy selected.

Results

Our analyses resulted in evaluations of 94.12% (95% CI 0.71–0.99) for sensitivity, 5.26% (95% CI 0.01–0.26) for specificity, a predictive value of 47.06% (95% CI 0.29–0.65) for a positive response, a predictive value of 50% (95% CI 0.01–0.98) for a negative response, with an overall calculated predictive accuracy of 47.22% (95% CI 0.30–0.64).

Conclusions

This is the first reported estimation of predictive accuracy derived from combining chemosensitivity and tumor gene expression analyses on liquid biopsy-derived CTCs, transiently cultured in vitro which, despite limitations, represents a baseline and benchmark which we envisage will be improve upon by methodological and technological advances and future clinical trials.

Ex Vivo Chemosensitivity Profiling of Acute Myeloid Leukemia and Its Correlation With Clinical Response and Outcome to Chemotherapy

We evaluated the predictive value of the ex-vivo PharmaFlow PM platform in measuring the pharmacological activity of drug combinations consisting of 20 different chemotherapy regimens (20 Tx) administered in 104 acute myeloid leukemia (AML) patients. The predicted sensitivities of alternative treatments for each patient were ranked in five 20% categories, from resistant to sensitive (Groups 1–5). The complete remission (CR) rates of the five groups were 0%, 12.5%, 38.5%, 50.0%, and 81.3%, respectively. The heat map showed a good relationship between drug sensitivity with CR (Group 4 + 5 vs. Group 1 + 2+3: 77.5% vs. 27.3%, p = 0.002) and the European Leukemia Net risk group (22.6% vs. 63.6%, p = 0.015). The predicted coincidence rate was 90.9% in Group 1 + 2 and 81.3% in Group 5. According to the recommendations of the PharmaFlow PM platform, the CR rate would have increased by about 16.3% in one cycle. The overall survival (OS) was shorter in patients predicted to be resistant (Group 1 + 2 vs. Group 3 + 4+5, p = 0.086). In multivariable analysis, CR after one cycle was an independent prognostic factor for OS [p = 0.001; 95% CI 0.202 (0.080–0.511)], and ex-vivo chemosensitivity was a potential predictive factor for OS [p = 0.078; 95% CI 0.696 (0.465–1.041)]. To conclude, the PharmaFlow PM platform is a rapid and valuable tool for predicting clinical response and outcomes in AML patients.

Chemosensitivity analysis and study of gene resistance on tumors and cancer stem cell isolates from patients with colorectal cancer

Colorectal cancer (CRC) is one of the main causes of mortality. Recent studies suggest that cancer stem cells (CSCs) can survive after chemotherapy and promote tumor invasiveness and aggression. According to a higher hierarchy complexity of CSC, different protocols for isolation, expansion, and characterization have been used; however, there are no available resistance biomarkers that allow predicting the clinical response of treatment 5‑fluorouracil (5FU) and oxaliplatin. Therefore, the primary aim of the present study was to analyze the expression of gene resistance on tumors and CSC‑derived isolates from patients CRC. In the present study, adenocarcinomas of the colon and rectum (CRAC) were classified based on an in vitro adenosine triphosphate‑based chemotherapy response assay, as sensitive and resistant and the percentage of CD24 and CD44 markers are evaluated by immunohistochemistry. To isolate resistant colon‑CSC, adenocarcinoma tissues resistant to 5FU and oxaliplatin were evaluated. Finally, all samples were sequenced using a custom assay with chemoresistance‑associated genes to find a candidate gene on resistance colon‑CSC. Results showed that 59% of the CRC tissue analyzed was resistant and had a higher percentage of CD44 and CD24 markers. An association was found in the expression of some genes between the tumor‑resistant tissue and CSC. Overall, isolates of the CSC population CD44+ resistant to 5FU and oxaliplatin demonstrated different expression profiles; however, the present study was able to identify overexpression of the KRT‑18 gene, in most of the isolates. In conclusion, the results of the present study showed overexpression of KRT‑18 in CD44+ cells is associated with chemoresistance to 5FU and oxaliplatin in CRAC.

ONCOGRAM: study protocol for the evaluation of therapeutic response and survival of metastatic colorectal cancer patients treated according to the guidelines of a chemosensitivity assay, the Oncogramme®

BACKGROUND

Colorectal cancer is a major public concern, being the second deadliest cancer in the world. Whereas survival is high for localized forms, metastatic colorectal cancer has showed poor prognosis, with a 5-year survival barely surpassing 11%. Conventional chemotherapies against this disease proved their efficiency and remain essential in first-line treatment. However, the large number of authorized protocols complexifies treatment decision. In common practice, such decision is made on an empirical basis, by assessing benefits and risks for the patient. In other words, there is currently no efficient means of predicting the efficacy of any chemotherapy protocol for metastatic colorectal cancer.

METHODS/DESIGN

The use of a chemosensitivity assay, the Oncogramme®, should help clinicians administer the best chemotherapy regimen to their patients. We hypothesize it would ultimately improve their survival. In this multicentred, prospective trial (ONCOGRAM), eligible patients with metastatic colorectal cancer are randomized to determine whether they will receive an Oncogramme®. For clinicians whose patients benefited from the assay (arm A), results are used as a decision support tool. Patients not undergoing the Oncogramme® procedure are treated according to current practice, without the assistance of the assay (arm B). Primary outcome is 1-year progression-free survival. Secondary outcomes include response rates, as well as 6-month and 1-year survival rates.

DISCUSSION

This study aims at investigating the clinical utility of the Oncogramme® as a decision support tool for the treatment of patients with metastatic colorectal cancer. If the Oncogramme® positively influenced patient overall survival and/or progression-free survival, it would be of great value for clinicians to implement this assay within the current landscape of personalized medicine tools, which include genomics and biomarker assays.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT03133273 . Registered on April 28, 2017.

Precision Medicine Gains Momentum: Novel 3D Models and Stem Cell-Based Approaches in Head and Neck Cancer

Despite the current progress in the development of new concepts of precision medicine for head and neck squamous cell carcinoma (HNSCC), in particular targeted therapies and immune checkpoint inhibition (CPI), overall survival rates have not improved during the last decades. This is, on the one hand, caused by the fact that a significant number of patients presents with late stage disease at the time of diagnosis, on the other hand HNSCC frequently develop therapeutic resistance. Distinct intratumoral and intertumoral heterogeneity is one of the strongest features in HNSCC and has hindered both the identification of specific biomarkers and the establishment of targeted therapies for this disease so far. To date, there is a paucity of reliable preclinical models, particularly those that can predict responses to immune CPI, as these models require an intact tumor microenvironment (TME). The "ideal" preclinical cancer model is supposed to take both the TME as well as tumor heterogeneity into account. Although HNSCC patients are frequently studied in clinical trials, there is a lack of reliable prognostic biomarkers allowing a better stratification of individuals who might benefit from new concepts of targeted or immunotherapeutic strategies. Emerging evidence indicates that cancer stem cells (CSCs) are highly tumorigenic. Through the process of stemness, epithelial cells acquire an invasive phenotype contributing to metastasis and recurrence. Specific markers for CSC such as CD133 and CD44 expression and ALDH activity help to identify CSC in HNSCC. For the majority of patients, allocation of treatment regimens is simply based on histological diagnosis and on tumor location and disease staging (clinical risk assessments) rather than on specific or individual tumor biology. Hence there is an urgent need for tools to stratify HNSCC patients and pave the way for personalized therapeutic options. This work reviews the current literature on novel approaches in implementing three-dimensional (3D) HNSCC in vitro and in vivo tumor models in the clinical daily routine. Stem-cell based assays will be particularly discussed. Those models are highly anticipated to serve as a preclinical prediction platform for the evaluation of stable biomarkers and for therapeutic efficacy testing.

Effect of oxaliplatin-based chemotherapy on chemosensitivity in patients with peritoneal metastasis from colorectal cancer treated with cytoreductive surgery and hyperthermic intraperitoneal chemotherapy: proof-of-concept study

Background

Chemosensitivity testing, including collagen gel droplet‐embedded culture drug sensitivity test, has proven to be a useful tool in therapeutic decision‐making. This retrospective analysis investigated chemosensitivity testing of peritoneal metastases collected during cytoreductive surgery (CRS), and its impact on survival in patients with colorectal cancer.

Methods

All patients with peritoneal metastasis from colorectal cancer who underwent CRS with or without hyperthermic intraperitoneal chemotherapy (HIPEC) between November 2008 and October 2014 were included. The growth inhibition rate was expressed as the ratio between the image density after treatment (T) and that before treatment (control, C). Tumours with a reduction in T/C ratio of less than 20 per cent were defined as resistant and those with a reduction of 20 per cent or more as sensitive. Groups were compared for overall (OS) and disease‐free (DFS) survival.

Results

Of 84 eligible patients, 81 received neoadjuvant chemotherapy (NACT), including 56 patients with an oxaliplatin‐based regimen. Mean(s.d.) follow‐up was 23·4(22·9) months. The median overall survival of all patients was 19·0 (i.q.r. 5·7–36·1) months, with a progression‐free survival time of 10·1 (4·5–17·0) months. Patients who received oxaliplatin‐based NACT had significantly altered chemosensitivity to oxaliplatin; only 20 of 51 such patients showed chemosensitivity to oxaliplatin compared with 16 of 24 who did not undergo oxaliplatin‐based NACT (P = 0·046). However, patients who showed chemoresistance to oxaliplatin had similar OS to those with chemosensitivity (18·8 versus 18·1 months; P = 0·835). The choice of HIPEC agents in patients who received oxaliplatin‐based NACT did not significantly influence survival (oxaliplatin versus mitomycin C: median OS 20·6 (10·9–24·8) versus 19·0 (10·5–34·6) months, P = 0·811; DFS 6·6 (2·8–25·7) versus 9·3 (4·1–13·9) months, P = 0·191).

Conclusion

Patients who had oxaliplatin‐based NACT showed a higher rate of chemoresistance to oxaliplatin at the time of CRS and HIPEC. The impact of chemosensitivity testing on OS remains unclear and needs further investigation.

Ex Vivo Culture Models to Indicate Therapy Response in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is characterized by a poor 5 year survival and varying response rates to both standard-of-care and new treatments. Despite advances in medicine and treatment methods, mortality rates have hardly decreased in recent decades. Reliable patient-derived tumor models offer the chance to predict therapy response in a personalized setting, thereby improving treatment efficacy by identifying the most appropriate treatment regimen for each patient. Furthermore, ex vivo tumor models enable testing of novel therapies before introduction in clinical practice. A literature search was performed to identify relevant literature describing three-dimensional ex vivo culture models of HNSCC to examine sensitivity to chemotherapy, radiotherapy, immunotherapy and targeted therapy. We provide a comprehensive overview of the currently used three-dimensional ex vivo culture models for HNSCC with their advantages and limitations, including culture success percentage and comparison to the original tumor. Furthermore, we evaluate the potential of these models to predict patient therapy response.

Predicting likelihood of in vivo chemotherapy response in canine lymphoma using ex vivo drug sensitivity and immunophenotyping data in a machine learning model

We report a precision medicine platform that evaluates the probability of chemotherapy drug efficacy for canine lymphoma by combining ex vivo chemosensitivity and immunophenotyping assays with computational modelling. We isolated live cancer cells from fresh fine needle aspirates of affected lymph nodes and collected post‐treatment clinical responses in 261 canine lymphoma patients scheduled to receive at least 1 of 5 common chemotherapy agents (doxorubicin, vincristine, cyclophosphamide, lomustine and rabacfosadine). We used flow cytometry analysis for immunophenotyping and ex vivo chemosensitivity testing. For each drug, 70% of treated patients were randomly selected to train a random forest model to predict the probability of positive Veterinary Cooperative Oncology Group (VCOG) clinical response based on input variables including antigen expression profiles and treatment sensitivity readouts for each patient's cancer cells. The remaining 30% of patients were used to test model performance. Most models showed a test set ROC‐AUC > 0.65, and all models had overall ROC‐AUC > 0.95. Predicted response scores significantly distinguished (P < .001) positive responses from negative responses in B‐cell and T‐cell disease and newly diagnosed and relapsed patients. Patient groups with predicted response scores >50% showed a statistically significant reduction (log‐rank P < .05) in time to complete response when compared to the groups with scores <50%. The computational models developed in this study enabled the conversion of ex vivo cell‐based chemosensitivity assay results into a predicted probability of in vivo therapeutic efficacy, which may help improve treatment outcomes of individual canine lymphoma patients by providing predictive estimates of positive treatment response.

Feasibility study of in vitro drug sensitivity assay of advanced non-small cell lung adenocarcinomas

Background Despite improved screening techniques, diagnosis of lung cancer is often late and its prognosis is poor. In the present study, in vitro chemosensitivity of solid tumours and pleural effusions of lung adenocarcinomas were analysed and compared with clinical drug response.Methods Tumour cells were isolated from resected solid tumours or pleural effusions, and cryopreserved. Three-dimensional (3D) tissue aggregate cultures were set up when the oncoteam reached therapy decision for individual patients. The aggregates were then treated with the selected drug or drug combination and in vitro chemosensitivity was tested individually measuring ATP levels. The clinical response to therapy was assessed by standard clinical evaluation over an 18 months period.Results Based on the data, the in vitro chemosensitivity test results correlate well with clinical treatment response.Conclusions Such tests if implemented into the clinical decision making process might allow the selection of an even more individualised chemotherapy protocol which could lead to better therapy response.

Cisplatin treatment induced interleukin 6 and 8 production alters lung adenocarcinoma cell migration in an oncogenic mutation dependent manner

BACKGROUND

The predominant metastatic site of lung cancer (LC) is the brain. Although outdated, conventional cisplatin treatment is still the main therapeutic approach for patients with advanced non-small cell lung cancer (NSCLC), since targeted therapy that offers better tumor control is not always possible. In the present study brain metastasis associated cytokine expression was investigated in primary NSCLC adenocarcinoma (AC) tissues with known oncogenic mutations in the presence or absence of platina based and tyrosine kinase inhibitor (TKI) drugs.

METHODS

Primary lung tumor samples were isolated, DNA was sequenced and then the samples were grouped based on mutation. Experiments were also performed using KRAS mutant A549 and EGFR mutant PC-9 cells. Drug response was analyzed in three dimensional (3D) tissue cultures. We assessed drug response and IL-6 and IL-8 cytokine expression in relation to cellular invasion using ATP dependent cell viability, qRT-PCR analysis, cytokine bead array, and migration assay.

RESULTS

In 3D co-cultures, primary NSCLC derived cells harboring EGFR mutation responded better to erlotinib treatment than KRAS mutant or KRAS/EGFR wild type (WT) cancer cells. In contrast, under the same culture conditions KRAS/EGFR WT or KRAS mutant cancer cells are more sensitive to cisplatin than EGFR mutant cells. Drug response and pro-inflammatory cytokine production varied depending on the driver mutations. Cisplatin but not erlotinib increased both IL-6 and IL-8 secretion and only IL-6 increased cellular migration and proliferation.

CONCLUSION

In vitro assays are available to determine the response to planned therapeutic approach of lung cancer subtypes. The sequence of administration of therapeutic drugs determines cytokine production and therefore therapeutic response.

Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia

Drug susceptibility (also called chemosensitivity) is an important criterion for developing a therapeutic strategy for various cancer types such as breast cancer and leukemia. Recently, functional assays such as high-content screening together with genomic analysis have been shown to be effective for predicting drug susceptibility, but their clinical applicability is poor since they are time-consuming (several days long), labor-intensive, and costly. Here we present a highly simple, rapid, and cost-effective liquid biopsy for ex vivo drug-susceptibility testing of leukemia. The method is based on an extreme-throughput (>1 million cells per second), label-free, whole-blood imaging flow cytometer with a deep convolutional autoencoder, enabling image-based identification of the drug susceptibility of every single white blood cell in whole blood within 24 hours by simply flowing a drug-treated whole blood sample as little as 500 μL into the imaging flow cytometer without labeling. Our results show that the method accurately evaluates the drug susceptibility of white blood cells from untreated patients with acute lymphoblastic leukemia. Our method holds promise for affordable precision medicine.

Live Cell Mass Accumulation Measurement Non-Invasively Predicts Carboplatin Sensitivity in Triple-Negative Breast Cancer Patient-Derived Xenografts

Prompt and repeated assessments of tumor sensitivity to available therapeutics could reduce patient morbidity and mortality by quickly identifying therapeutic resistance and optimizing treatment regimens. Analysis of changes in cancer cell biomass has shown promise in assessing drug sensitivity and fulfilling these requirements. However, a major limitation of previous studies in solid tumors, which comprise 90% of cancers, is the use of cancer cell lines rather than freshly isolated tumor material. As a result, existing biomass protocols are not obviously extensible to real patient tumors owing to potential artifacts that would be generated by the removal of cells from their microenvironment and the deleterious effects of excision and purification. In this present work, we show that simple excision of human triple-negative breast cancer (TNBC) tumors growing in immunodeficient mouse, patient-derived xenograft (PDX) models, followed by enzymatic disaggregation into single cell suspension, is enabling for rapid and accurate biomass accumulation-based predictions of in vivo sensitivity to the chemotherapeutic drug carboplatin. We successfully correlate in vitro biomass results with in vivo treatment results in three TNBC PDX models that have differential sensitivity to this drug. With a maximum turnaround time of 40 h from tumor excision to useable results and a fully-automated analysis pipeline, the assay described here has significant potential for translation to clinical practice.

Ex vivo activity of cytotoxic drugs and targeted agents in small intestinal neuroendocrine tumors

Small intestinal neuroendocrine tumors (SI-NETs) are generally considered resistant to systemic treatment. To date, predictive markers for drug activity are lacking. Tumor samples from 27 patients with SI-NETs were analyzed ex vivo for sensitivity to a panel of cytotoxic drugs and targeted agents using a short-term total cell kill assay. Samples of renal cancer, colorectal cancer (CRC), ovarian cancer and chronic lymphocytic leukemia (CLL) were included for comparison. For the SI-NET subset, drug sensitivity was analyzed in relation to clinicopathological variables and pre-treatment biomarkers. For cytotoxic drugs, SI-NETs demonstrated similar or higher sensitivity to 5-FU, platinum, gemcitabine and doxorubicin compared with CRC. For several of the targeted kinase inhibitors, SI-NET was among the most sensitive solid tumor types. CLL and ovarian cancer were generally the most sensitive tumor types to both cytotoxic drugs and protein kinase inhibitors. SI-NET was more sensitive to the mTOR inhibitor sirolimus than the other solid tumor types tested. Individual SI-NET samples demonstrated great variability in ex vivo sensitivity for most drugs. Cross-resistance between different drugs also varied considerably, being higher among protein kinase inhibitors. Age, stage, grade, peritoneal carcinomatosis and extra-abdominal metastases as well as serum chromogranin A and urine 5-HIAA concentrations at diagnosis did not correlate to drug sensitivity ex vivo SI-NETs exhibit intermediate sensitivity ex vivo to cytotoxic and targeted drugs. Clinicopathological factors and currently used biomarkers are not clearly associated to ex vivo sensitivity, challenging these criteria for treatment decisions in SI-NET. The great variability in drug sensitivity calls for individualized selection of therapy.