). † These authors contributed equally to this work. SUMMARYVarious mutant screens have been undertaken to identify constituents involved in the transmission of signals from the plastid to the nucleus. Many of these screens have been performed using carotenoid-deficient plants grown in the presence of norflurazon (NF), an inhibitor of phytoene desaturase. NF-treated plants are bleached and suppress the expression of nuclear genes encoding chloroplast proteins. Several genomes uncoupled (gun) mutants have been isolated that de-repress the expression of these nuclear genes. In the present study, a genetic screen has been established that circumvents severe photo-oxidative stress in NF-treated plants. Under these modified screening conditions, happy on norflurazon (hon) mutants have been identified that, like gun mutants, de-repress expression of the Lhcb gene, encoding a light-harvesting chlorophyll protein, but, in contrast to wild-type and gun mutants, are green in the presence of NF. hon mutations disturb plastid protein homeostasis, thereby activating plastid signaling and inducing stress acclimatization. Rather than defining constituents of a retrograde signaling pathway specifically associated with the NF-induced suppression of nuclear gene expression, as proposed for gun, hon mutations affect Lhcb expression more indirectly prior to initiation of plastid signaling in NF-treated seedlings. They pre-condition seedlings by inducing stress acclimatization, thereby attenuating the impact of a subsequent NF treatment.

Neighborhoods encompass complex environments comprised of unique economic, physical, and social characteristics that have a profound impact on the residing individual's health and, collectively, on the community's wellbeing. Neighborhood disadvantage (ND) is one of several factors that prominently contributes to racial breast cancer (BC) health disparities in American women. African American (AA) women develop more aggressive breast cancer features, such as triple-negative receptor status and more advanced histologic grade and tumor stage, and suffer worse clinical outcomes than European American (EA) women. While the adverse effects of neighborhood disadvantage on health, including increased risk of cancer and decreased longevity, have recently come into focus, the specific molecular mechanisms by which neighborhood disadvantage increase BC risk and worsen BC outcomes (survivorship, recurrence, mortality) are not fully elucidated. This review illuminates the probable biological links between neighborhood disadvantage and predominantly BC risk, with an emphasis on stress reactivity and inflammation, epigenetics and telomere length in response to adverse neighborhood conditions.

As the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to surge worldwide, our knowledge of coronavirus disease 2019 (COVID-19) is rapidly expanding. Although most COVID-19 patients recover within weeks of symptom onset, some experience lingering symptoms that last for months ("long COVID-19"). Early reports of COVID-19 sequelae, including cardiovascular, pulmonary, and neurological conditions, have raised concerns about the long-term effects of COVID-19, especially in hard-hit communities. It is becoming increasingly evident that cancer patients are more susceptible to SARS-CoV-2 infection and are at a higher risk of severe COVID-19 than the general population. Nevertheless, whether long COVID-19 increases the risk of cancer in those with no prior malignancies, remains unclear.Given, the disproportionate impact of the disease on the African American community, yet another unanswered question is whether racial disparities are to be expected in COVID-19 sequelae. Herein, we propose that long COVID-19 may predispose recovered patients to cancer development and accelerate cancer progression. This hypothesis is based on growing evidence of the ability of SARS-CoV-2 to modulate oncogenic pathways, promote chronic low-grade inflammation, and cause tissue damage. Comprehensive studies are urgently required to elucidate the effects of long COVID-19 on cancer susceptibility.

The stark racial disparities related to the COVID-19 pandemic in the U.S., wherein minority populations are disproportionately getting infected and succumbing to the disease, is of grave concern. It is critical to understand and address the underlying causes of these disparities that are complex and driven by interacting environmental, social and biological factors. In this article we focus on the AA community and examine how social and environmental determinants of health intersect with biological factors (comorbidities, underlying genetics, host immunity, vitamin D levels, epigenetics) to exacerbate risk for morbidity and mortality.

ImportanceIncreasing evidence suggests that low socioeconomic status and geographic residence in disadvantaged neighborhoods contribute to disparities in breast cancer outcomes. However, little epidemiological research has sought to better understand these disparities within the context of location.ObjectiveTo examine the association between neighborhood deprivation and racial disparities in mortality among Black and White patients with breast cancer in the state of Georgia.Design, Setting, and ParticipantsThis population-based cohort study collected demographic and geographic data from patients diagnosed with breast cancer between January 1, 2004, and February 11, 2020, in 3 large health care systems in Georgia. A total of 19 580 patients with breast cancer were included: 12 976 from Piedmont Healthcare, 2285 from Grady Health System, and 4319 from Emory Healthcare. Data were analyzed from October 2, 2020, to August 11, 2022.ExposuresArea deprivation index (ADI) scores were assigned to each patient based on their residential census block group. The ADI was categorized into quartile groups, and associations between ADI and race and ADI × race interaction were examined.Main Outcomes and MeasuresCox proportional hazards regression models were used to compute hazard ratios (HRs) and 95% CIs associating ADI with overall mortality by race. Kaplan-Meier curves were used to visualize mortality stratified across racial and ADI groups.ResultsOf the 19 580 patients included in the analysis (mean [SD] age at diagnosis, 58.8 [13.2] years), 3777 (19.3%) died during the course of the study. Area deprivation index contributed differently to breast cancer outcomes for Black and White women. In multivariable-adjusted models, living in a neighborhood with a greater ADI (more deprivation) was associated with increased mortality for White patients with breast cancer; compared with the ADI quartile of less than 25 (least deprived), increased mortality HRs were found in quartiles of 25 to 49 (1.22 [95% CI, 1.07-1.39]), 50 to 74 (1.32 [95% CI, 1.13-1.53]), and 75 or greater (1.33 [95% CI, 1.07-1.65]). However, an increase in the ADI quartile group was not associated with changes in mortality for Black patients with breast cancer (quartile 25 to 49: HR, 0.81 [95% CI, 0.61-1.07]; quartile 50 to 74: HR, 0.91 [95% CI, 0.70-1.18]; and quartile ≥75: HR, 1.05 [95% CI, 0.70-1.36]). In neighborhoods with an ADI of 75 or greater, no racial disparity was observed in mortality (HR, 1.11 [95% CI, 0.92-1.36]).Conclusions and RelevanceBlack women with breast cancer had higher mortality than White women in Georgia, but this disparity was not explained by ADI: among Black patients, low ADI was not associated with lower mortality. This lack of association warrants further investigation to inform community-level approaches that may mitigate the existing disparities in breast cancer outcomes in Georgia.

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The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient’s tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. “The future is already here—it’s just not very evenly distributed.”-William Ford Gibson

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