Between-tumor and within-tumor heterogeneity in invasive potential

Abstract

For women with access to healthcare and early detection, breast cancer deaths are caused primarily by metastasis rather than growth of the primary tumor. Metastasis has been difficult to study because it happens deep in the body, occurs over years, and involves a small fraction of cells from the primary tumor. Furthermore, within-tumor heterogeneity relevant to metastasis can also lead to therapy failures and is obscured by studies of bulk tissue. Here we exploit heterogeneity to identify molecular mechanisms of metastasis. We use "organoids", groups of hundreds of tumor cells taken from a patient and grown in the lab, to probe tumor heterogeneity, with potentially thousands of organoids generated from a single tumor. We show that organoids have the character of biological replicates: within-tumor and between-tumor variation are of similar magnitude. We develop new methods based on population genetics and variance components models to build between-tumor and within-tumor statistical tests, using organoids analogously to large sibships and vastly amplifying the test power. We show great efficiency for tests based on the organoids with the most extreme phenotypes and potential cost savings from pooled tests of the extreme tails, with organoids generated from hundreds of tumors having power predicted to be similar to bulk tests of hundreds of thousands of tumors. We apply these methods to an association test for molecular correlates of invasion, using a novel quantitative invasion phenotype calculated as the spectral power of the organoid boundary. These new approaches combine to show a strong association between invasion and protein expression of Keratin 14, a known biomarker for poor prognosis, with p = 2 × 10 −45 for within-tumor tests of individual organoids and p < 10 −6 for pooled tests of extreme tails. Future studies using these methods could lead to discoveries of new classes of cancer targets and development of corresponding therapeutics. All data and methods are available under an open source license at https://github.com/ baderzone/invasion_2019.

Intratumoral Heterogeneity Promotes Collective Cancer Invasion through NOTCH1 Variation

“…Heterogeneity in invasiveness among microtumors has been reported in organoid invasion models [35]. Similarly, we observed only a portion of microtumors penetrated the gel despite the microtumors were formed by a single cell line.…”

Intratumoral Heterogeneity Promotes Collective Cancer Invasion Through NOTCH1 Variation

“…Heterogeneity in invasiveness among microtumors has been reported in organoid invasion models (Padmanaban et al, 2020). Similarly, we observed only a portion of microtumors penetrated the gel despite the microtumors were formed by a single cell line.…”

Cancer cells educate natural killer cells to a metastasis-promoting cell state

“…In this study, we sought to understand the cellular and molecular basis of NK cell–cancer cell interactions during breast cancer metastasis. Prior work from our laboratory revealed that clusters of K14 + cancer cells pioneer collective invasion and distant metastasis across breast cancer subtypes ( Cheung et al, 2013 , 2016 ; Cheung and Ewald, 2016 ) and that K14 expression correlates with quantitative measures of invasion in human breast tumor samples ( Padmanaban et al, 2020 ). Here we show that NK cells are the most abundant early responder to cancer cell clusters in the lung, that K14 + cancer cells typically lack MHC class I expression, and that hNK cells preferentially target K14 + cancer cells for cytotoxic death.…”