Online accounts of gene expression profiling in early-stage breast cancer: Interpreting genomic testing for chemotherapy decision making

Enrolling the body as active agent in cancer treatment: Tracing immunotherapy metaphors and materialities

Immunotherapy is heralded as the 'fifth pillar' of cancer therapy, after surgery, radiotherapy, chemotherapy and genomic medicine. It involves 'harnessing' patients' own immune system T-cells to treat cancer. In this article, I draw on qualitative interviews with practitioners working in oncology and patients in the UK, to trace metaphorical and discursive framing around immunotherapy. Immunotherapy aims to restore the functioning of the immune system to detect cancer (non-self), working with the self/non-self model that pervades immunology discourse more widely. Practitioners draw on metaphors that cement this self/non-self model, and that tend to depict the relationship between cancer and the immune system as an internal battle. Yet the discursive framing around immunotherapy also involves shifts that emphasize the body's own capacity to heal, where it is framed as 'gentle' or 'tolerable' on the body. Through this discursive shift, immunotherapy refigures the antagonism associated with the self/non-self model in the context of cancer. Analysing patients' embodied experiences of treatment, this article attends to the material realities and tensions provoked by this shift in discursive framing. This article contributes to feminist STS analyses of immunology discourse, and extends this literature by arguing that it is critical to address the material stakes of these discursive shifts by paying attention to patients' day-to-day experiences of treatment. The discursive framing of immunotherapy brings into being new forms of embodied patienthood in the context of cancer.

Regulating diagnosis-Molecular and regulatory sub-stratifications of lung cancer treatment

The sociology of diagnosis has shown that diagnosis not only serves to label the underlying cause of disease but also to provide access to services and resources. Elaborating on this double-affordance of diagnosis, this article examines how precision medicine reconfigures diagnosis as a label and as a process in regulatory and clinical settings. Reporting from an ethnographic case study of the introduction of immunotherapy for lung cancer, the paper unfolds the uncertainties involved in dissecting diagnosis into layers and examines the efforts and negotiations it takes to enable these layers to work both as clinical entities and regulative entities with the purpose of delineating access to treatment. I suggest that the work of subdividing diseases into molecularly defined categories for the purpose of delineating treatment-eligible populations can be labelled 'diagnostic sub-stratification' and argue that it is pertinent to understand the political capacity of this strategy. Diagnostic sub-stratification involves a push of diagnosis from the clinic 'up' into the regulatory system and 'out' into the laboratories, obscuring who is accountable for the diagnostic categories employed to define patients' treatment access.

Unsettling the treatment imperative? Chemotherapy decision-making in the wake of genomic techniques

Social scientists have argued that a treatment imperative shapes experiences of biomedicine. This is evident within oncology, where discourses of hope are tempered by persistent fears surrounding cancer. It is within this context that genomic decision-making tools are entering routine care. These may indicate that a treatment is not appropriate for a particular disease profile. We draw on qualitative interviews and observations centred on gene expression profiling to consider the implications of this technique for the treatment imperative in early breast cancer. Influenced by sociological perspectives on medical technologies, we discuss how fallibilities of established tools have forged a space for the introduction of genomic testing into chemotherapy decision-making. We demonstrate how high expectations shaped patients' interpretations of this tool as facilitating the 'right' treatment choice. We then unpick these accounts, highlighting the complex relationship between gene expression profiling and treatment decision-making. We argue that anticipations for genomic testing to provide certainty in treatment choice must account for the sociocultural and organisational contexts in which it is used, including the powerful entwinement of chemotherapy and cancer. Our research has implications for sociological perspectives on treatment decision-making and clinical expectations for genomic medicine to resolve the 'problem' of overtreatment.

Extending Adjuvant Endocrine Therapy for 10 Years: A Mixed-Methods Analysis of Women's Decision Making in an Online Breast Cancer Forum

An additional 5 years of treatment with adjuvant hormonal therapy, to complete 10 years of medication, is recommended to reduce the risk of breast cancer recurrence. Yet professionals and patients should balance this benefit against side effects and toxicities. Little is known about women’s decision making regarding persistence with extended endocrine therapy. In this study, we collected data from a UK online breast cancer forum to analyse patterns of persistence and its associated factors. A mixed-methods exploratory sequential design was used, with a qualitative analysis of text (n = 61 individuals) informing the development of a quantitative instrument to statistically analyse the prevalence of the findings (n = 130). Our findings identified three different groups of women who had to make decisions regarding persistence with treatment: those about to complete 5 years of therapy, those who decided to extend treatment, and those who were initially prescribed 10 years. Factors affecting persistence were, lack of self-efficacy in managing side effects, lack of reassurance about individual risk of recurrence, and impact on quality of life. Interventions such as training of healthcare professionals including risk communication, medication reviews by clinical pharmacists, and re-planning of services in follow-up care, should better support women’s needs in extended hormonal therapy.

Diagnostic layering: Patient accounts of breast cancer classification in the molecular era

Social scientific work has considered the promise of genomic medicine to transform healthcare by personalising treatment. However, little qualitative research attends to already well-established molecular techniques in routine care. In this article we consider women's experiences of routine breast cancer diagnosis in the UK NHS. We attend to patient accounts of the techniques used to subtype breast cancer and guide individual treatment. We introduce the concept of 'diagnostic layering' to make sense of how the range of clinical techniques used to classify breast cancer shape patient experiences of diagnosis. The process of diagnostic layering, whereby various levels of diagnostic information are received by patients over time, can render diagnosis as incomplete and subject to change. In the example of early breast cancer, progressive layers of diagnostic information are closely tied to chemotherapy recommendations. In recent years a genomic test, gene expression profiling, has become introduced into routine care. Because gene expression profiling could indicate a treatment recommendation where standard tools had failed, the technique could represent a 'final layer' of diagnosis for some patients. However, the test could also invalidate previous understandings of the cancer, require additional interpretation and further prolong the diagnostic process. This research contributes to the sociology of diagnosis by outlining how practices of cancer subtyping shape patient experiences of breast cancer. We add to social scientific work attending to the complexities of molecular and genomic techniques by considering the blurring of diagnostic and therapeutic activities from a patient perspective.

GSIAR: gene-subcategory interaction-based improved deep representation learning for breast cancer subcategorical analysis using gene expression, applicable for precision medicine

Tumor subclass detection and diagnosis is inevitable requirement for personalized medical treatment and refinement of the effects that the somatic cells show towards other clinical conditions. The genome of these somatic cells exhibits mutations and genetic variations of the breast cancer cells and helps in understanding the characteristic behavior of the cancer cells. But their analysis is limited to clustering and there is requirement to analyze what else can be done with the data for identifying the tumor subcategory and the stages of subclasses. In this work, we have extended the work with similar data (consisting of 105 breast tumor cell lines) to solve other detection and characterization problems through computation and intelligent representation learning. Most of our work comprises of systematic data cleaning, analysis, and building prediction models with deep computational architectures and establish that the transformed data can help in better distinction of the respective categories. Our main contribution is the novel gene-subcategory interaction-based regularization (GSIAR) based data selection and analysis concept, alongside the prediction, proven to enhance the performance of the classification techniques. Graphical Abstract A graphical abstract of our model - Gene-subcategory interaction affinity-based regularization (GSIAR).

Genomics and breast cancer screening

Many women fear the risk of developing breast cancer, and some women have increased fear because of their family history. Thankfully, the study of genetics has brought forth tools to better identify women at risk. An understanding of genetics and cancer has led to genetic testing protocols which enable at-risk women to take preventative action through medication, surgery, and intensive screenings. These protocols not only have the potential to prevent cancer but also lead to early detection. Appropriate screening for women at risk for genetic breast cancer is essential for patient care. These screenings include specific risk assessment tests, genetic counseling, and genetic testing. To provide the best possible care for patients, providers must have a basic understanding of cancer, genetics, screening tests, genetic testing, and available prevention measures.

Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature

OBJECTIVES

With the explosive growth in availability of health data captured using non-traditional sources, the goal for this work was to evaluate the current biomedical literature on theory- driven studies investigating approaches that leverage non- traditional data in personalized medicine applications.

METHODS

We conducted a literature assessment guided by the personalized medicine unsolicited health information (pUHl) conceptual framework incorporating diffusion of innovations and task-technology fit theories.

RESULTS

The assessment provided an oveiview of the current literature and highlighted areas for future research. In particular, there is a need for: more research on the relationship between attributes of innovation and of societal structure on adoption; new study designs to enable flexible communication channels; more work to create and study approaches in healthcare settings; and more theory-driven studies with data-driven interventions.

CONCLUSION

This work introduces to an informatics audience an elaboration on personalized medicine implementation with non-traditional data sources by blending it with the pUHl conceptual framework to help explain adoption. We highlight areas to pursue future theory-driven research on personalized medicine applications that leverage non-traditional data sources.

Online accounts of gene expression profiling in early-stage breast cancer: Interpreting genomic testing for chemotherapy decision making

Background

Genomic techniques are being developed within oncology and beginning to be experienced within routine cancer care. Little is known about how these tools feature in patients’ experiences of treatment decision making.

Objective

This research explores the ways in which women interpret and discuss gene expression profiling for breast cancer treatment decision making, as articulated within online accounts.

Design

This study used a qualitative approach to analyse written exchanges focusing on gene expression profiling in the UK (Oncotype DX test). Accounts are taken from online forums hosted by two UK cancer charity websites, comprising 132 discussion threads from a total of seven forums. Authors qualitatively analysed the data and developed key themes drawing on existing literature from medical sociology.

Findings

Women used online spaces to share and discuss results of gene expression profiling. Women interpreted results in the context of indirect experience of cancer treatment, and sociocultural depictions of cancer and chemotherapy. Users largely represented the test positively, emphasizing its ability to “personalize” treatment pathways, though many also pointed to inherent uncertainties with regards the possibility of cancer recurrence.

Discussion and Conclusions

We highlight the complex contexts in which genomic techniques are experienced, with these shaped by personal biographies, online environments and pervasive cultural narratives of cancer and its treatment. We highlight tensions between the claims of genomic testing to aid treatment decision making and patient reflections on the capability of these techniques to resolve uncertainties surrounding treatment decisions.