Variability In Treatment Response Research Articles

Can quantifying the extent of ‘high grade’ features help explain prognostic variability in anaplastic astrocytoma?

Purpose Both phenotypic and genotypic variations now underpin glioma classification, thus helping to more accurately guide their clinical management. However, WHO Grade III anaplastic astrocytoma (AA) remains an unpredictable, heterogeneous entity; displaying a variable prognosis, clinical course and treatment response. This study aims to examine whether additional tumour characteristics influence either overall survival (OS) or 3-year survival in AA. Materials and methods Data were collected on all newly diagnosed cases of AA between 2003 and 2014, followed up for a minimum of 3 years. Molecular information was obtained from case records and if missing, was re-analysed. Histological slides were independently examined for Ki-67 proliferation index, cellularity and number of mitotic figures. Kaplan–Meier and Cox regression analyses were used to assess OS. Results In total, 50 cases were included with a median OS of 14.5 months (range: 1–150 months). Cumulative 3-year survival was 31.5%. Median age was 50 years (range: 24 − 77). Age, IDH1 mutation status, lobar location, oncological therapy and surgical resection were significant independent prognostic indicators for OS. In cases demonstrating an OS ≥ 3 years (n = 15), Ki-67 index, number of mitotic figures and percentage areas of ‘high cellularity’ were significantly reduced, i.e. more characteristic of lower-grade/WHO Grade II glioma. Conclusions IDH1 status, age, treatment and location remain the most significant prognostic indicators for patients with AA. However, Ki-67 index, mitotic figures and cellularity may help identify AA cases more likely to survive < 3 years, i.e. AA cases more similar to glioblastoma and those cases more likely to survive > 3 years, i.e. more similar to a low-grade glioma.

Lessons Learned in a Community-Based, Randomized Controlled Trial of a Complicated Grief Intervention

Complicated grief (CG), severe, prolonged (>12 months) grieving, disproportionately affects older adults. A prospective two-group, waitlisted RCT examined whether four sessions of Accelerated Resolution Therapy (ART) was effective in informal caregivers by comparing pre-to-post ART changes and investigating variation in treatment response by baseline CG levels. Inclusion: ≥60 years, Inventory of Complicated Grief >25. Paired t-tests of mean (SD) differences compared pre- to post-ART; pre-ART to 8-week follow-up, and post-ART to 8-week follow-up; then stratified by median baseline level of CG. Mean (SD) age of 54 participants was 68.7 (7.2) years, 85% female, and 93% white. Significantly greater CG reduction (-22.8 (10.3)) vs. waitlist (-4.3 (6.0)) was found. Within-participant effect sizes from baseline to 8-weeks post treatment were 1.96 (95% CI: 1.45, 2.47; p<0.0001). Treatment effects did not substantially differ by baseline levels. Lesson learned was that it was possible to successfully recruit and treat CG in the community.

Biomarkers to Personalize the Treatment of Rheumatoid Arthritis: Focus on Autoantibodies and Pharmacogenetics.

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is very complex and heterogeneous. If not adequately treated, RA patients are likely to manifest excess of morbidity and disability with an important impact on the quality of life. Pharmacological treatment is based on the administration of the disease-modifying antirheumatic drugs (DMARDs), subdivided into conventional synthetic (csDMARDs), targeted synthetic (tsDMARDs), and biological (bDMARDs). bDMARDs are now frequently administered in patients, both as alternative treatment and together with csDMARDs. Unfortunately, there is a therapeutic response variability both to old and new drugs. Therefore, to identify pre-therapeutic and on-treatment predictors of response is a priority. This review aims to summarize recent advances in understanding the causes of the variability in treatment response in RA, with particular attention to predictive potential of autoantibodies and DMARD pharmacogenetics. In recent years, several biomarkers have been proposed to personalize the therapy. Unfortunately, a magic bullet does not exist, as many factors concur to disease susceptibility and treatment outcomes, acting around the patient’s congenital background. Models integrating demographic, clinical, biochemical, and genetic data are needed to enhance the predictive capacity of specific factors singularly considered to optimize RA treatment in light of multidisciplinary patient management.

Pharmacogenetics of inflammatory bowel disease.

Patients with inflammatory bowel disease (IBD) show large variability in disease course, and also treatment response. The variability in treatment response has led to many initiatives in search of genetic markers to optimize treatment and avoid severe side effects. This has been very successful for thiopurines, one of the drugs used to induce and maintain remission in IBD. However, for the newer treatment options for IBD, like biologicals, the search for genetic predictors has not yielded any candidate biomarkers with clinical utility. In this review, a summary of recent advances in pharmacogenetics focusing on thiopurines and anti-TNF agents is given.

Phenotypic and Functional Characterization of Multiple Myeloma By Single Cell Mass Cytometry (CyTOF)

Phenotypic and Functional Characterization of Multiple Myeloma By Single Cell Mass Cytometry (CyTOF)

Expression profiling of cultured podocytes exposed to nephrotic plasma reveals intrinsic molecular signatures of nephrotic syndrome.

Background Nephrotic syndrome (NS) is a common renal disorder in children attributed to podocyte injury. However, children with the same diagnosis have markedly variable treatment responses, clinical courses, and outcomes, suggesting molecular heterogeneity.Purpose This study aimed to explore the molecular responses of podocytes to nephrotic plasma to identify specific genes and signaling pathways differentiating various clinical NS groups as well as biological processes that drive injury in normal podocytes. Methods Transcriptome profiles from immortalized human podocyte cell line exposed to the plasma of 8 subjects (steroid-sensitive nephrotic syndrome [SSNS], n=4; steroid-resistant nephrotic syndrome [SRNS], n=2; and healthy adult individuals [control], n=2) were generated using microarray analysis. Results Unsupervised hierarchical clustering of global gene expression data was broadly correlated with the clinical classification of NS. Differential gene expression (DGE) analysis of diseased groups (SSNS or SRNS) versus healthy controls identified 105 genes (58 up-regulated, 47 down-regulated) in SSNS and 139 genes (78 up-regulated, 61 down-regulated) in SRNS with 55 common to SSNS and SRNS, while the rest were unique (50 in SSNS, 84 genes in SRNS). Pathway analysis of the significant (P≤0.05, -1≤ log2 FC ≥1) differentially expressed genes identified the transforming growth factor-β and Janus kinase-signal transducer and activator of transcription pathways to be involved in both SSNS and SRNS. DGE analysis of SSNS versus SRNS identified 2,350 genes with values of P≤0.05, and a heatmap of corresponding expression values of these genes in each subject showed clear differences in SSNS and SRNS. Conclusion Our study observations indicate that, although podocyte injury follows similar pathways in different clinical subgroups, the pathways are modulated differently as evidenced by the heatmap. Such transcriptome profiling with a larger cohort can stratify patients into intrinsic subtypes and provide insight into the molecular mechanisms of podocyte injury.

A Machine-Learning Tool Concurrently Models Single Omics and Phenome Data for Functional Subtyping and Personalized Cancer Medicine.

Simple SummaryTumours are heterogeneous that reflect variable patient prognosis and treatment responses (phenotypes). Since these variable phenotypes are outcomes of genomics, it is essential to integrate genome and phenome jointly. In this study, we report the development and application of a new machine learning tool (Phenotypic Mapping; PhenMap) to identify unsupervised clinically-relevant (functional) subtypes and biomarkers by simultaneously integrating clinical phenotypes and single omics data, mainly, transcriptome. This integrative analysis provides the opportunity to simultaneously identify robust and context-specific subtypes and associated phenotypes (that biologically explain each subtype) without statistically losing information. We demonstrate its utility using breast cancer cell lines and patient samples to identify functional subtypes associated with specific drug responses (including CD4/6 inhibitor) and prognosis. These subtypes may potentially predict clinical outcomes with further validation. This tool can be applied to other omics data such as methylomics, genomics and radiomics along with any phenotypic data.One of the major challenges in defining clinically-relevant and less heterogeneous tumor subtypes is assigning biological and/or clinical interpretations to etiological (intrinsic) subtypes. Conventional clustering/subtyping approaches often fail to define such subtypes, as they involve several discrete steps. Here we demonstrate a unique machine-learning method, phenotype mapping (PhenMap), which jointly integrates single omics data with phenotypic information using three published breast cancer datasets (n = 2045). The PhenMap framework uses a modified factor analysis method that is governed by a key assumption that, features from different omics data types are correlated due to specific “hidden/mapping” variables (context-specific mapping variables (CMV)). These variables can be simultaneously modeled with phenotypic data as covariates to yield functional subtypes and their associated features (e.g., genes) and phenotypes. In one example, we demonstrate the identification and validation of six novel “functional” (discrete) subtypes with differential responses to a cyclin-dependent kinase (CDK)4/6 inhibitor and etoposide by jointly integrating transcriptome profiles with four different drug response data from 37 breast cancer cell lines. These robust subtypes are also present in patient breast tumors with different prognosis. In another example, we modeled patient gene expression profiles and clinical covariates together to identify continuous subtypes with clinical/biological implications. Overall, this genome-phenome machine-learning integration tool, PhenMap identifies functional and phenotype-integrated discrete or continuous subtypes with clinical translational potential.

Pulmonary arterial hypertension: Rationale for using multiple vs. single drug therapy.

Pulmonary arterial hypertension (PAH) is defined by a heterogenous pathobiology that corresponds to variable clinical presentation, treatment response, and prognosis across affected patients. The approach to pharmacotherapeutics in PAH has evolved since the introduction of the first prostacyclin replacement drug, which was trialed in patients with end-stage disease as a strategy by which to delay or prevent mortality. Subsequently, the aim of care in PAH has shifted toward minimizing symptoms, improving functional capacity, delaying disease progression, and prolonging life. Thus, treatments are now implemented earlier and according to the evidence base, which spans more than twenty years and includes patients at various stages of disease. Overall, the evidence supports multidrug therapy rather than monotherapy in the majority of PAH patients. Among incident patients, up-front combination therapy with ambrisentan and tadalafil or other comparable agents within these drug classes is recommended based on strong clinical trial data. In the near future, up-front triple therapy may be emerge as bona fide treatment approach in selected patients. Future goals that are already under consideration in PAH include stronger integration of pathobiological characteristics when considering the use of specific drugs, or the development of novel therapies, toward precision medicine-based clinical pharmacology.

Co-Occurring Psychopathology Moderates Social Skills Improvement in a Randomized Controlled Trial of a Collaborative School-Home Intervention for Children with ADHD

ABSTRACT Objective Children with ADHD often exhibit marked impairment in their social skills, but evidence-based psychosocial interventions for ADHD have shown limited efficacy in remediating these deficits. Co-occurring psychopathology exacerbates social deficits in children with ADHD and is a plausible moderator of treatment response. To identify factors contributing to variable social skills treatment response, we examined co-occurring externalizing, depression, and anxiety symptoms as moderators of social skills outcomes in a randomized controlled trial of the Collaborative Life Skills (CLS) program, an evidence-based collaborative school-home ADHD intervention. Method Participants were 159 children with ADHD (M age = 8.35 years, 28.3% female) at 27 schools in an urban public school district. Twenty-three schools were randomly assigned to CLS or usual services, with an additional four schools assigned to Spanish-adapted CLS or usual services. Multi-informant measures of co-occurring psychopathology and social skills were collected at baseline and post-treatment. Results Parent-rated externalizing and depression symptoms moderated treatment effects on social skills, whereby higher symptomatology in each domain was unrelated to social skills improvement in the CLS group but predicted worsening social skills in response to usual services. In contrast, teacher-rated anxiety moderated treatment effects on social skills, whereby higher anxiety predicted greater social skills improvement in response to CLS but was unrelated to social skills outcomes following usual services. Conclusions Findings reflect novel evidence that child psychopathology domains exhibit unique moderating effects on social skills treatment response in children with ADHD. We discuss implications for optimizing evidence-based interventions to target social impairment in this population.

Population characteristics as important contextual factors in rheumatological trials: an exploratory meta-epidemiological study from an OMERACT Working Group

ObjectivesTo explore whether trial population characteristics modify treatment responses across various interventions, comparators and rheumatic conditions.MethodsIn this meta-epidemiological study, we included trials from systematic reviews available from the Cochrane Musculoskeletal...

Pharmacologic Advancement in Schizophrenia

Schizophrenia is a disorder of mental debility characterized by abnormal social behavior in which person is unable to recognize reality. The sign and symptoms are variable and heterogeneous. Due to the diverse symptoms and variable treatment response, it is challenging to treat. Recent advancements in genomic, epidemiology and neurosciences can provide the appropriate medicines and treatments for minimizing symptoms and consequences of schizophrenia. This literature review was highlights the etiology, pathophysiology, neurotransmitter system, novel treatment and management of schizophrenia.The mainstay treatment of schizophrenic patients included antipsychotic drug with psychotherapy, social rehabilitation and job training

T2 Hepatocellular Carcinoma Exception Policies That Prolong Waiting Time Improve the Use of Evidence-based Treatment Practices.

A United Network for Organ Sharing policy change in 2015 created a 6-mo delay in the receipt of T2 hepatocellular carcinoma exception points. It was hypothesized that the policy changed locoregional therapy (LRT) practices and explant findings because of longer expected waiting time. Patients transplanted with a first T2 hepatocellular carcinoma exception application between January 1, 2010 and December 31, 2014 (prepolicy; N = 6562), and those between August 10, 2015 and December 2, 2019 (postpolicy; N = 2345), were descriptively compared using data from United Network for Organ Sharing. Median time from first application to transplantation was more homogenous across the US postpolicy, due to greater absolute increases in Regions 3, 6, 10, and 11 (>120 d). During waitlisting, postpolicy candidates received more LRT overall (P < 0.001), with more notable increases in previously short-wait regions. Postpolicy explants were overall more likely to have ≥1 tumor with complete necrosis (23.9 versus 18.4%; P < 0.001) and less likely have ≥1 tumor with no necrosis (32.6% versus 38.5%; P < 0.001). Significant geographic variability in explant treatment response was observed prepolicy with recipients in previously short-wait regions having more frequent tumor viability at transplant. Postpolicy, there were no differences in the prevalence of recipients with ≥1 tumor with 100% or 0% necrosis across regions (P = 0.9 and 0.2, respectively). The 2015 T2 exception policy has led to reduced geographic variability in the use of pretransplant LRT and in less frequent tumor viability on explant for recipients in previously short-waiting times.

Aqueous outflow imaging techniques and what they tell us about intraocular pressure regulation.

Recent advances in the medical and surgical management of open-angle glaucoma have increased the number of treatment options available. Several new intraocular pressure (IOP)-lowering treatments target the conventional aqueous outflow (AO) system. However, success rates are variable and outcomes in individual patients are often difficult to predict. Variable treatment responses remain unexplained and highlight deficiencies in our current understanding of AO regulation and IOP homeostasis. Imaging is often relied upon to confirm diagnoses and monitor treatment responses in other ocular and systemic pathologies. As yet no suitable AO imaging tool has been developed to fulfil this role in glaucoma. A variety of imaging techniques have been used to study the AO tracts of humans and animals in ex vivo and in vivo eyes. In this review, results from novel imaging techniques that assess aqueous drainage through the episcleral venous system are considered and we argue these provide new insights into AO regulation. We suggest that the ability to objectively measure AO responses to interventions would be a significant clinical advance, and we have demonstrated that this can be achieved with direct visualisation of aqueous drainage. We predict that the evolution of AO imaging technology will continue to reveal critical components of AO and IOP regulation, and that personalised IOP-lowering treatment in glaucoma care may well become a reality in the near future.

Abstract 1313: Genomic and transcriptomic profiles of primary prostate cancer identify unique targets for therapeutic intervention

Abstract The tumor microenvironment and genomic landscape of intermediate and high-risk primary localized prostate cancers are clinically heterogeneous and result in variable treatment response in individuals. Cancer-specific alterations at DNA and RNA level is a critical driver of intra-tumoral heterogeneity that significantly impacts the molecular processes which influence the path of disease progression and outcome. In this study, we have performed genomic and transcriptomic analysis of 267 primary prostate cancer. Our analysis revealed actionable alterations and gene signatures for risk stratification and decision support. Clinically significant variants were detected in DNA repair (HR and Mismatch pathway), PI3/AKT, and TP53 signaling pathways with a strong association with disease progression. Further, single-cell analysis (scRNA-seq) of prostate cancer that progressed to metastasis post-therapy identified the unique tumor and immune cell-clusters. Functional annotation of these clusters and drug repurposing studies revealed novel targets for therapeutic intervention that was validated using organoid cultures. Our studies show that an Integrated analysis using genomic, clinical, and pathological features has the potential to define prostate cancer subtypes or phenotypes associated with poor prognosis. Our approach can advance prostate cancer treatment in patients with adverse clinical features by providing treatment options beyond the standard of care (surgery or radiation) and with better therapeutic benefit. Citation Format: Dimple Chakravarty, Zichen Wang, Michael Rossi, Parita Ratnani, Boris Reva, Dmitry Rykunov, Kamala Bhatt, Vinayak Wagaskar, Rachel Weil, Kristin Beaumont, Michael Beaumont, Avi Maayan, Robert Sebra, Nina Bhardwaj, Sujit S. Nair, Ashutosh K. Tewari. Genomic and transcriptomic profiles of primary prostate cancer identify unique targets for therapeutic intervention [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1313.

Using l-Carnitine as a Pharmacologic Probe of the Interpatient and Metabolic Variability of Sepsis.

The objective of this review is to discuss the therapeutic use and differential treatment response to Levo-carnitine (l-carnitine) treatment in septic shock, and to demonstrate common lessons learned that are important to the advancement of precision medicine approaches to sepsis. We propose that significant interpatient variability in the metabolic response to l-carnitine and clinical outcomes can be used to elucidate the mechanistic underpinnings that contribute to sepsis heterogeneity. A narrative review was conducted that focused on explaining interpatient variability in l-carnitine treatment response. Relevant biological and patient-level characteristics considered include genetic, metabolic, and morphomic phenotypes; potential drug interactions; and pharmacokinetics (PKs). Despite promising results in a phase I study, a recent phase II clinical trial of l-carnitine treatment in septic shock showed a nonsignificant reduction in mortality. However, l-carnitine treatment induces significant interpatient variability in l-carnitine and acylcarnitine concentrations over time. In particular, administration of l-carnitine induces a broad, dynamic range of serum concentrations and measured peak concentrations are associated with mortality. Applied systems pharmacology may explain variability in drug responsiveness by using patient characteristics to identify pretreatment phenotypes most likely to derive benefit from l-carnitine. Moreover, provocation of sepsis metabolism with l-carnitine offers a unique opportunity to identify metabolic response signatures associated with patient outcomes. These approaches can unmask latent metabolic pathways deranged in the sepsis syndrome and offer insight into the pathophysiology, progression, and heterogeneity of the disease. The compiled evidence suggests there are several potential explanations for the variability in carnitine concentrations and clinical response to l-carnitine in septic shock. These serve as important confounders that should be considered in interpretation of l-carnitine clinical studies and broadly holds lessons for future clinical trial design in sepsis. Consideration of these factors is needed if precision medicine in sepsis is to be achieved.

Abstract B17: Hyperactivating the Hippo pathway effector TAZ distorts the immune microenvironment in promoting the mesenchymal transformation in glioblastoma

Abstract Glioblastoma (GBM), the deadliest and most common primary brain malignancy in adults, is highly heterogeneous with variable prognoses and treatment responses. The mesenchymal subtype of GBM is associated with the worst prognosis and highest treatment resistance. It is still not clear how GBM mesenchymal differentiation is achieved. Hyperactivity of transcriptional coactivator with PDZ-binding motif (TAZ) was linked to the GBM mesenchymal transformation, although its role in this process remains unclear. Here, by using orthotopic xenograft mouse GBM models, we found that hyperactive TAZ in tumor cells promotes myeloid cells to infiltrate into tumors. Such enhanced myeloid cell infiltration is associated with the mesenchymal transformation and tumor progression. We demonstrated that these TAZ-induced tumorigenic properties rely on its interaction with the transcription factor, TEA domain family member (TEAD). Such interaction induces the transcription of chemokines that are able to recruit the myeloid cells. Specific depletion of the infiltrated myeloid cells is able to slow down the tumor progression. Our studies suggested that recruiting myeloid cells by hyperactive TAZ contributes the mesenchymal transformation and tumor progression in glioblastoma. Citation Format: Patricia Yee, Yiju Wei, Zhijun Liu, Wei Li. Hyperactivating the Hippo pathway effector TAZ distorts the immune microenvironment in promoting the mesenchymal transformation in glioblastoma [abstract]. In: Proceedings of the AACR Special Conference on the Hippo Pathway: Signaling, Cancer, and Beyond; 2019 May 8-11; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(8_Suppl):Abstract nr B17.

Approach to the patient with acute severe autoimmune hepatitis.

SummaryAutoimmune hepatitis is associated with varied clinical presentations and natural history, as well as somewhat unpredictable treatment responses. Understanding how to stratify patients who require further escalation of therapy will help clinicians manage these patients. The presentation of acute severe autoimmune hepatitis (AS-AIH) is relatively uncommon, although its prevalence is potentially greater than currently perceived. Previous studies consist of small retrospective single-centre series and are not directly comparable due to the diversity of presentations, disease definitions and non-standardised treatment regimens. We define AS-AIH as those who present acutely with AIH and are icteric with an international normalised ratio ≥1.5 and no evidence of hepatic encephalopathy. Those with hepatic encephalopathy should be defined as having AS-AIH with acute liver failure. In this review, we provide a structured practical approach for diagnosing and managing this unique group of patients.

The genetics of rheumatoid arthritis.

RA is a chronic systemic inflammatory disease that primarily affects the small joints of the hands and feet, and results in a mean reduction in life expectancy of 3-10 years. RA is a multigene disorder with a substantial genetic component and a heritability estimate of 60%. Large-scale Genome-Wide Association Studies (GWAS) and meta-analyses have revealed common disease-associated variants in the population that may contribute cumulatively to RA pathogenesis. This review identifies the most significant genetic variants associated with RA susceptibility to date, with particular focus on the contribution of the HLA class II genes across different ethnic groups. Also discussed are the potential applications of pharmacogenomics to RA management by identifying polymorphisms associated with variation in treatment response or toxicity. The use of genetic variants to guide treatment strategy has the potential to not only reduce National Health Service costs, but also drastically improve patient experience and quality of life.

Single-Cell-Derived Primary Rectal Carcinoma Cell Lines Reflect Intratumor Heterogeneity Associated with Treatment Response.

The standard treatment of patients with locally advanced rectal cancer consists of preoperative chemoradiotherapy (CRT) followed by surgery. However, the response of individual tumors to CRT is extremely diverse, presenting a clinical dilemma. This broad variability in treatment response is likely attributable to intratumor heterogeneity (ITH). We addressed the impact of ITH on response to CRT by establishing single-cell-derived cell lines (SCDCL) from a treatment-naïve rectal cancer biopsy after xenografting. Individual SCDCLs derived from the same tumor responded profoundly different to CRT in vitro. Clonal reconstruction of the tumor and derived cell lines based on whole-exome sequencing revealed nine separate clusters with distinct proportions in the SCDCLs. Missense mutations in SV2A and ZWINT were clonal in the resistant SCDCL, but not detected in the sensitive SCDCL. Single-cell genetic analysis by multiplex FISH revealed the expansion of a clone with a loss of PIK3CA in the resistant SCDCL. Gene expression profiling by tRNA-sequencing identified the activation of the Wnt, Akt, and Hedgehog signaling pathways in the resistant SCDCLs. Wnt pathway activation in the resistant SCDCLs was confirmed using a reporter assay. Our model system of patient-derived SCDCLs provides evidence for the critical role of ITH for treatment response in patients with rectal cancer and shows that distinct genetic aberration profiles are associated with treatment response. We identified specific pathways as the molecular basis of treatment response of individual clones, which could be targeted in resistant subclones of a heterogenous tumor.

Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients.

Objectives Type 2 Diabetes mellitus is a progressive metabolic disease characterized by relative insulin insufficiency and insulin resistance resulting in hyperglycemia. Despite the widespread use of metformin, there is considerable variation in treatment response; with approximately one-third of patients failing to achieve adequate glycemic control. Studies have reported the involvement of single nucleotide polymorphisms and their interactions in genetic pathways i.e., pharmacodynamics and pharmacokinetics. This study aims to investigate the association between 19 pharmacogenetics biomarkers and response to metformin treatment. Methods MassARRAY panels were designed and optimized by Inqaba Biotechnical Industries, to genotype 19 biomarkers for 140 type 2 diabetic outpatients. Results The CT genotype of the rs12752688 polymorphism was significantly associated with increased response to metformin therapy after correction (OR=0.33, 95% CI [0.16-0.68], p-value=0.006). An association was also found between the GA genotype of SLC47A2 rs12943590 and a decreased response to metformin therapy after correction (OR=2.29, 95% CI [1.01-5.21], p-value=0.01). Conclusions This is the first study investigating the association between genetic variants and responsiveness to medication for diabetic patients from the indigenous Nguni population in South Africa. It is suggested that rs12752688 and rs12943590 be included in pharmacogenomics profiling systems to individualize metformin therapy for diabetic patients from African populations.