Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies.

Pancreatic cancer is a leading cause of cancer-related death, largely due to metastatic dissemination. We investigated pancreatic cancer progression by utilizing a mathematical framework of metastasis formation together with comprehensive data of 228 patients, 101 of whom had autopsies. We found that pancreatic cancer growth is initially exponential. After estimating the rates of pancreatic cancer growth and dissemination, we determined that patients likely harbor metastases at diagnosis and predicted the number and size distribution of metastases as well as patient survival. These findings were validated in an independent database. Finally, we analyzed the effects of different treatment modalities, finding that therapies that efficiently reduce the growth rate of cells earlier in the course of treatment appear to be superior to upfront tumor resection. These predictions can be validated in the clinic. Our interdisciplinary approach provides insights into the dynamics of pancreatic cancer metastasis and identifies optimum therapeutic interventions.

Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers.

BACKGROUND: Intratumor heterogeneity (ITH) in microsatellite instability-high (MSI-H) colorectal cancer (CRC) has been poorly studied. We aimed to clarify how the ITH of MSI-H CRCs is generated in cancer evolution and how immune selective pressure affects ITH. METHODS: We reanalyzed public whole-exome sequencing data on 246 MSI-H CRCs. In addition, we performed a multi-region analysis from 6 MSI-H CRCs. To verify the process of subclonal immune escape accumulation, a novel computational model of cancer evolution under immune pressure was developed. RESULTS: Our analysis presented the enrichment of functional genomic alterations in antigen-presentation machinery (APM). Associative analysis of neoantigens indicated the generation of immune escape mechanisms via HLA alterations. Multiregion analysis revealed the clonal acquisition of driver mutations and subclonal accumulation of APM defects in MSI-H CRCs. Examination of variant allele frequencies demonstrated that subclonal mutations tend to be subjected to selective sweep. Computational simulations of tumour progression with the interaction of immune cells successfully verified the subclonal accumulation of immune escape mutations and suggested the efficacy of early initiation of an immune checkpoint inhibitor (ICI) -based treatment. CONCLUSIONS: Our results demonstrate the heterogeneous acquisition of immune escape mechanisms in MSI-H CRCs by Darwinian selection, providing novel insights into ICI-based treatment strategies.

HLA Class I Analysis Provides Insight Into the Genetic and Epigenetic Background of Immune Evasion in Colorectal Cancer With High Microsatellite Instability.

BACKGROUND & AIMS: A detailed understanding of antitumor immunity is essential for optimal cancer immune therapy. Although defective mutations in the B2M and HLA-ABC genes, which encode molecules essential for antigen presentation, have been reported in several studies, the effects of these defects on tumor immunity have not been quantitatively evaluated. METHODS: Mutations in HLA-ABC genes were analyzed in 114 microsatellite instability-high colorectal cancers using a long-read sequencer. The data were further analyzed in combination with whole-exome sequencing, transcriptome sequencing, DNA methylation array, and immunohistochemistry data. RESULTS: We detected 101 truncating mutations in 57 tumors (50%) and loss of 61 alleles in 21 tumors (18%). Based on the integrated analysis that enabled the immunologic subclassification of microsatellite instability-high colorectal cancers, we identified a subtype of tumors in which lymphocyte infiltration was reduced, partly due to reduced expression of HLA-ABC genes in the absence of apparent genetic alterations. Survival time of patients with such tumors was shorter than in patients with other tumor types. Paradoxically, tumor mutation burden was highest in the subtype, suggesting that the immunogenic effect of accumulating mutations was counterbalanced by mutations that weakened immunoreactivity. Various genetic and epigenetic alterations, including frameshift mutations in RFX5 and promoter methylation of PSMB8 and HLA-A, converged on reduced expression of HLA-ABC genes. CONCLUSIONS: Our detailed immunogenomic analysis provides information that will facilitate the improvement and development of cancer immunotherapy.

Multifocal origin of occupational cholangiocarcinoma revealed by comparison of multilesion mutational profiles.

Recently identified occupational cholangiocarcinoma among printing workers is characterized by chronic bile duct injuries and precancerous or early cancerous lesions at multiple sites of the bile ducts. These observations suggested the potential multifocal carcinogenesis of the disease. We performed whole-exome analysis of multiple lesions, including the invasive carcinomas and precancerous lesions of four occupational cholangiocarcinoma cases. A much higher mutation burden was observed in both the invasive carcinomas (mean 76.3/Mb) and precancerous lesions (mean 71.8/Mb) than in non-occupational cholangiocarcinomas (mean 1.6/Mb). Most somatic mutations identified in 11 of 16 lesions did not overlap with each other. In contrast, a unique trinucleotide mutational signature of GpCpY to GpTpY was shared among the lesions. These results suggest that most of these lesions are multiclonal in origin and that common mutagenic processes, which may be induced by exposure to haloalkanes or their metabolites, generated somatic mutations at different sites of the bile ducts. A similarly high mutation rate had already been identified in the precancerous lesions, implying an increased potential for carcinogenesis throughout the biliary tree. These genomic features support the importance of ongoing close follow-up of the patients as a group at high risk of recurrence.

Metastatic seeding of human colon cancer cell clusters expressing the hybrid epithelial/mesenchymal state.

Emerging evidence supports the theory that tumor cell clusters efficiently metastasize to distant organs. However, the roles of epithelial-to-mesenchymal transition (EMT) in metastasizing tumor cell clusters have not yet been fully elucidated. To investigate this issue, tumor fragments were dissected from 40 colorectal cancer (CRC) patients and implanted subcutaneously into immunodeficient mice. We observed that tumors developed from the tumor fragments obtained from 28 of the 40 CRC patients. The tumors were then dissociated into cell suspensions to be orthotopically injected into secondary mice. The tumors from 13 of the 28 patients progressed. Furthermore, metastases formed spontaneously in the liver and lungs from the tumor fragments obtained from 8 of these 13 patients. Moreover, employing a mathematical analysis, we showed that tumor cell clusters seeded these metastases significantly more often than did single tumor cells. Membrane E-cadherin- and nuclear ZEB1-positive tumor cells indicating the hybrid epithelial/mesenchymal state were also detected in primary tumors of various CRC patients, and in the corresponding patient-derived xenografts (PDXs) and circulating tumor cell clusters in the bloodstreams of mice. In contrast, ZEB1 staining was barely detectable in the patient-matched liver metastases presumably developing through mesenchymal-to-epithelial transition. Inhibition of E-cadherin or ZEB1 expression by shRNA notably prevented the PDX-derived tumor organoids from colonizing the liver, when injected intrasplenically into mice, indicating E-cadherin and ZEB1 expressions to be required for their metastatic colonization. Taken together, these findings suggest that the epithelial/mesenchymal state mediates metastatic seeding of human CRC cell clusters into distant organs.

Correction: Integrated Multiregional Analysis Proposing a New Model of Colorectal Cancer Evolution.

[This corrects the article DOI: 10.1371/journal.pgen.1005778.].

Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients.

Human primary glioblastomas (GBM) often harbor mutations within the epidermal growth factor receptor (EGFR). Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.

Integrated Multiregional Analysis Proposing a New Model of Colorectal Cancer Evolution.

Understanding intratumor heterogeneity is clinically important because it could cause therapeutic failure by fostering evolutionary adaptation. To this end, we profiled the genome and epigenome in multiple regions within each of nine colorectal tumors. Extensive intertumor heterogeneity is observed, from which we inferred the evolutionary history of the tumors. First, clonally shared alterations appeared, in which C>T transitions at CpG site and CpG island hypermethylation were relatively enriched. Correlation between mutation counts and patients' ages suggests that the early-acquired alterations resulted from aging. In the late phase, a parental clone was branched into numerous subclones. Known driver alterations were observed frequently in the early-acquired alterations, but rarely in the late-acquired alterations. Consistently, our computational simulation of the branching evolution suggests that extensive intratumor heterogeneity could be generated by neutral evolution. Collectively, we propose a new model of colorectal cancer evolution, which is useful for understanding and confronting this heterogeneous disease.

A novel tumour-suppressor function for the Notch pathway in myeloid leukaemia.

Notch signalling is a central regulator of differentiation in a variety of organisms and tissue types. Its activity is controlled by the multi-subunit γ-secretase (γSE) complex. Although Notch signalling can play both oncogenic and tumour-suppressor roles in solid tumours, in the haematopoietic system it is exclusively oncogenic, notably in T-cell acute lymphoblastic leukaemia, a disease characterized by Notch1-activating mutations. Here we identify novel somatic-inactivating Notch pathway mutations in a fraction of patients with chronic myelomonocytic leukaemia (CMML). Inactivation of Notch signalling in mouse haematopoietic stem cells (HSCs) results in an aberrant accumulation of granulocyte/monocyte progenitors (GMPs), extramedullary haematopoieisis and the induction of CMML-like disease. Transcriptome analysis revealed that Notch signalling regulates an extensive myelomonocytic-specific gene signature, through the direct suppression of gene transcription by the Notch target Hes1. Our studies identify a novel role for Notch signalling during early haematopoietic stem cell differentiation and suggest that the Notch pathway can play both tumour-promoting and -suppressive roles within the same tissue.

Clonal evolution of hematopoietic stem cells after cancer chemotherapy.

Normal hematopoietic stem and progenitor cells (HSPCs) inherently accumulate somatic mutations and lose clonal diversity with age, processes implicated in the development of myeloid malignancies 1 . The impact of exogenous stressors, such as cancer chemotherapies, on the genomic integrity and clonal dynamics of normal HSPCs is not well defined. We conducted whole-genome sequencing on 1,032 single-cell-derived HSPC colonies from 10 patients with multiple myeloma (MM), who had undergone various chemotherapy regimens. Our findings reveal that melphalan treatment distinctly increases mutational burden with a unique mutation signature, whereas other MM chemotherapies do not significantly affect the normal mutation rate of HSPCs. Among these therapy-induced mutations were several oncogenic drivers such as TET2 and PPM1D . Phylogenetic analysis showed a clonal architecture in post-treatment HSPCs characterized by extensive convergent evolution of mutations in genes such as TP53 and PPM1D . Consequently, the clonal diversity and structure of post-treatment HSPCs mirror those observed in normal elderly individuals, suggesting an accelerated clonal aging due to chemotherapy. Furthermore, analysis of matched therapy-related myeloid neoplasm (t-MN) samples, which occurred 1-8 years later, enabled us to trace the clonal origin of t-MNs to a single HSPC clone among a group of clones with competing malignant potential, indicating the critical role of secondary mutations in dictating clonal dominance and malignant transformation. Our findings suggest that cancer chemotherapy promotes an oligoclonal architecture with multiple HSPC clones possessing competing leukemic potentials, setting the stage for the selective emergence of a singular clone that evolves into t-MNs after acquiring secondary mutations. These results underscore the importance of further systematic research to elucidate the long-term hematological consequences of cancer chemotherapy.

A race between tumor immunoescape and genome maintenance selects for optimum levels of (epi)genetic instability.

The human immune system functions to provide continuous body-wide surveillance to detect and eliminate foreign agents such as bacteria and viruses as well as the body's own cells that undergo malignant transformation. To counteract this surveillance, tumor cells evolve mechanisms to evade elimination by the immune system; this tumor immunoescape leads to continuous tumor expansion, albeit potentially with a different composition of the tumor cell population ("immunoediting"). Tumor immunoescape and immunoediting are products of an evolutionary process and are hence driven by mutation and selection. Higher mutation rates allow cells to more rapidly acquire new phenotypes that help evade the immune system, but also harbor the risk of an inability to maintain essential genome structure and functions, thereby leading to an error catastrophe. In this paper, we designed a novel mathematical framework, based upon the quasispecies model, to study the effects of tumor immunoediting and the evolution of (epi)genetic instability on the abundance of tumor and immune system cells. We found that there exists an optimum number of tumor variants and an optimum magnitude of mutation rates that maximize tumor progression despite an active immune response. Our findings provide insights into the dynamics of tumorigenesis during immune system attacks and help guide the choice of treatment strategies that best inhibit diverse tumor cell populations.

Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles.

Introduction: Local and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known. Methods: This study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge. Results: We report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type. Discussion: Our study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention.

Mathematical analysis identifies the optimal treatment strategy for epidermal growth factor receptor-mutated non-small cell lung cancer.

Introduction: In Asians, more than half of non-small cell lung cancers (NSCLC) are induced by epidermal growth factor receptor (EGFR) mutations. Although patients carrying EGFR driver mutations display a good initial response to EGFR-Tyrosine Kinase Inhibitors (EGFR-TKIs), additional mutations provoke drug resistance. Hence, predicting tumor dynamics before treatment initiation and formulating a reasonable treatment schedule is an urgent challenge. Methods: To overcome this problem, we constructed a mathematical model based on clinical observations and investigated the optimal schedules for EGFR-TKI therapy. Results: Based on published data on cell growth rates under different drugs, we found that using osimertinib that are efficient for secondary resistant cells as the first-line drug is beneficial in monotherapy, which is consistent with published clinical statistical data. Moreover, we identified the existence of a suitable drug-switching time; that is, changing drugs too early or too late was not helpful. Furthermore, we demonstrate that osimertinib combined with erlotinib or gefitinib as first-line treatment, has the potential for clinical application. Finally, we examined the relationship between the initial ratio of resistant cells and final cell number under different treatment conditions, and summarized it into a therapy suggestion map. By performing parameter sensitivity analysis, we identified the condition where　osimertinib-first therapy was recommended as the optimal treatment option. Discussion: This study for the first time theoretically showed the optimal treatment strategies based on the known information in NSCLC. Our framework can be applied to other types of cancer in the future.

A progenitor cell origin of myeloid malignancies.

All cancers rely on cells that have properties of long-term self-renewal or "stemness" to maintain and propagate the tumor, but the cell of origin of most cancers is still unknown. Here, we design a stochastic mathematical model of hematopoietic stem and progenitor cells to study the evolutionary dynamics of cancer initiation. We consider different evolutionary pathways leading to cancer-initiating cells in JAK2V617F-positive myeloproliferative neoplasms (MPN): (i) the JAK2V617F mutation may arise in a stem cell; (ii) a progenitor cell may first acquire a mutation conferring self-renewal, followed by acquisition of the JAK2V617F mutation; (iii) the JAK2V617F mutation may first emerge in a progenitor cell, followed by a mutation conferring self-renewal; and (iv) a mutation conferring self-renewal to progenitors may arise in the stem cell population without causing a change in the stem cell's phenotype, followed by the JAK2V617F mutation emerging in a progenitor cell. We find mathematical evidence that a progenitor is the most likely cell of origin of JAK2V617F-mutant MPN. These results may also have relevance to other tumor types arising in tissues that are organized as a differentiation hierarchy.

Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin.

The accurate and early diagnosis and classification of cancer origin from either tissue or liquid biopsy is crucial for selecting the appropriate treatment and reducing cancer-related mortality. Here, we established the CAncer Cell-of-Origin (CACO) methylation panel using the methylation data of the 28 types of cancer in The Cancer Genome Atlas (7950 patients and 707 normal controls) as well as healthy whole blood samples (95 subjects). We showed that the CACO methylation panel had high diagnostic potential with high sensitivity and specificity in the discovery (maximum AUC = 0.998) and validation (maximum AUC = 1.000) cohorts. Moreover, we confirmed that the CACO methylation panel could identify the cancer cell type of origin using the methylation profile from liquid as well as tissue biopsy, including primary, metastatic, and multiregional cancer samples and cancer of unknown primary, independent of the methylation analysis platform and specimen preparation method. Together, the CACO methylation panel can be a powerful tool for the classification and diagnosis of cancer.

Mathematical Modeling of Locoregional Recurrence Caused by Premalignant Lesions Formed Before Initial Treatment.

Locoregional recurrence after surgery is a major unresolved issue in cancer treatment. Premalignant lesions are considered a cause of cancer recurrence. A study showed that premalignant lesions surrounding the primary tumor drove a high local cancer recurrence rate after surgery in head and neck cancer. Based on the multistage theory of carcinogenesis, cells harboring an intermediate number of mutations are not cancer cells yet but have a higher risk of becoming cancer than normal cells. This study constructed a mathematical model for cancer initiation and recurrence by combining the Moran and branching processes in which cells require two specific mutations to become malignant. There are three populations in this model: (i) normal cells with no mutation, (ii) premalignant cells with one mutation, and (iii) cancer cells with two mutations. The total number of healthy tissue is kept constant to represent homeostasis, and there is a rare chance of mutation every time a cell divides. If a cancer cell with two mutations arises, the cancer population proliferates, violating the homeostatic balance of the tissue. Once the number of cancer cells reaches a certain size, we conduct computational resection and remove the cancer cell population, keeping the ratio of normal and premalignant cells in the tissue unchanged. After surgery, we considered tissue dynamics and eventually observed the second appearance of cancer cells as recurrence. Consequently, we computationally revealed the conditions where the time to recurrence became short by parameter sensitivity analysis. Particularly, when the premalignant cells' fitness is higher than normal cells, the proportion of premalignant cells becomes large after the surgical resection. Moreover, the mathematical model was fitted to clinical data on disease-free survival of 1,087 patients in 23 cancer types from the TCGA database. Finally, parameter values of tissue dynamics are estimated for each cancer type, where the likelihood of recurrence can be elucidated. Thus, our approach provides insights into the concept to identify the patients likely to experience recurrence as early as possible.

A CDC7 inhibitor sensitizes DNA-damaging chemotherapies by suppressing homologous recombination repair to delay DNA damage recovery.

Cell division cycle 7 (CDC7), a serine/threonine kinase, plays important roles in DNA replication. We developed a highly specific CDC7 inhibitor, TAK-931, as a clinical cancer therapeutic agent. This study aimed to identify the potential combination partners of TAK-931 for guiding its clinical development strategies. Unbiased high-throughput chemical screening revealed that the highest synergistic antiproliferative effects observed were the combinations of DNA-damaging agents with TAK-931. Functional phosphoproteomic analysis demonstrated that TAK-931 suppressed homologous recombination repair activity, delayed recovery from double-strand breaks, and led to accumulation of DNA damages in the combination. Whole-genome small interfering RNA library screening identified sensitivity-modulating molecules, which propose the experimentally predicted target cancer types for the combination, including pancreatic, esophageal, ovarian, and breast cancers. The efficacy of combination therapy in these cancer types was preclinically confirmed in the corresponding primary-derived xenograft models. Thus, our findings would be helpful to guide the future clinical strategies for TAK-931.

Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas.

Isocitrate dehydrogenase-mutant low-grade gliomas (IDHmut-LGG) grow slowly but frequently undergo malignant transformation, which eventually leads to premature death. Chemotherapy and radiotherapy treatments prolong survival, but can also induce genetic (or epigenetic) alterations involved in transformation. Here, we developed a mathematical model of tumor progression based on serial tumor volume data and treatment history of 276 IDHmut-LGGs classified by chromosome 1p/19q codeletion (IDHmut/1p19qcodel and IDHmut/1p19qnoncodel) and performed genome-wide mutational analyses, including targeted sequencing and longitudinal whole-exome sequencing data. These analyses showed that tumor mutational burden correlated positively with malignant transformation rate, and chemotherapy and radiotherapy significantly suppressed tumor growth but increased malignant transformation rate per cell by 1.8 to 2.8 times compared with before treatment. This model revealed that prompt adjuvant chemoradiotherapy prolonged malignant transformation-free survival in small IDHmut-LGGs (≤ 50 cm3). Furthermore, optimal treatment differed according to genetic alterations for large IDHmut-LGGs (> 50 cm3); adjuvant therapies delayed malignant transformation in IDHmut/1p19qnoncodel but often accelerated it in IDHmut/1p19qcodel. Notably, PI3K mutation was not associated with malignant transformation but increased net postoperative proliferation rate and decreased malignant transformation-free survival, prompting the need for adjuvant therapy in IDHmut/1p19qcodel. Overall, this model uncovered therapeutic strategies that could prevent malignant transformation and, consequently, improve overall survival in patients with IDHmut-LGGs. SIGNIFICANCE: A mathematical model successfully estimates malignant transformation-free survival and reveals a link between genetic alterations and progression, identifying precision medicine approaches for optimal treatment of IDH-mutant low-grade gliomas.

The evolution of tumor metastases during clonal expansion.

Cancer is a leading cause of morbidity and mortality in many countries. Solid tumors generally initiate at one particular site called the primary tumor, but eventually disseminate and form new colonies in other organs. The development of such metastases greatly diminishes the potential for a cure of patients and is thought to represent the final stage of the multi-stage progression of human cancer. The concept of early metastatic dissemination, however, postulates that cancer cell spread might arise early during the development of a tumor. It is important to know whether metastases are present at diagnosis since this determines treatment strategies and outcome. In this paper, we design a stochastic mathematical model of the evolution of tumor metastases in an expanding cancer cell population. We calculate the probability of metastasis at a given time during tumor evolution, the expected number of metastatic sites, and the total number of cancer cells as well as metastasized cells. Furthermore, we investigate the effect of drug administration and tumor resection on these quantities and predict the survival time of cancer patients. The model presented in this paper allows us to determine the probability and number of metastases at diagnosis and to identify the optimum treatment strategy to maximally prolong survival of cancer patients.

Combination treatment with a PI3K/Akt/mTOR pathway inhibitor overcomes resistance to anti-HER2 therapy in PIK3CA-mutant HER2-positive breast cancer cells.

Amplification and/or overexpression of human epidermal growth factor receptor 2 (HER2) are observed in 15-20% of breast cancers (HER2+ breast cancers), and anti-HER2 therapies have significantly improved prognosis of patients with HER2+ breast cancer. One resistance mechanism to anti-HER2 therapies is constitutive activation of the phosphoinositide 3-kinase (PI3K) pathway. Combination therapy with small-molecule inhibitors of AKT and HER2 was conducted in HER2+ breast cancer cell lines with or without PIK3CA mutations, which lead to constitutive activation of the PI3K pathway. PIK3CA mutations played important roles in resistance to single-agent anti-HER2 therapy in breast cancer cell lines. Combination therapy of a HER2 inhibitor and an AKT inhibitor, as well as other PI3K pathway inhibitors, could overcome the therapeutic limitations associated with single-agent anti-HER2 treatment in PIK3CA-mutant HER2+ breast cancer cell lines. Furthermore, expression of phosphorylated 4E-binding protein 1 (p4EBP1) following the treatment correlated with the antiproliferative activities of the combination, suggesting that p4EBP1 may have potential as a prognostic and/or efficacy-linking biomarkers for these combination therapies in patients with HER2+ breast cancer. These findings highlight potential clinical strategies using combination therapy to overcome the limitations associated with single-agent anti-HER2 therapies in patients with HER2+ breast cancer.