You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:

- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.
- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.
- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.

Please format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.

As an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:

[["artesunate", "artemether", "COMB"], ["Nifedipine", "Labetalol", "Prazosin", "POS"]]

The paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.

In your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.

paragraph: Trastuzumab reverses letrozole resistance and amplifies the sensitivity of breast cancer cells to estrogen. In this study, we investigated adaptive mechanisms associated with aromatase inhibitor (AI) resistance in breast cancer cells and show that sensitivity to AIs can be extended through dual inhibition of estrogen receptor (ER) and human epidermal receptor-2 (Her-2) signaling. We used human ER-positive breast cancer cells stably transfected with the aromatase gene (MCF-7Ca). These cells grow as tumors in nude mice and are inhibited by AIs. Despite continued treatment, tumors eventually become insensitive to AI letrozole. The cells isolated from these long-term letrozole-treated tumors (LTLT-Ca) were found to have decreased ERalpha levels. Our results suggest that LTLT-Ca cells survive estrogen deprivation by activation of Her-2/mitogen-activated protein kinase (MAPK) pathway. Here, we show that trastuzumab (antibody against Her-2; IC(50) = 0.4 mg/mL) was very effective in restoring the ERalpha levels and sensitivity of LTLT-Ca cells to endocrine therapy by down-regulation of Her-2/MAPK pathway and up-regulation of ERalpha. In contrast, trastuzumab was ineffective in the parental hormone-responsive MCF-7Ca cells (IC(50) = 4.28 mg/mL) and xenografts. By blocking Her-2, trastuzumab also up-regulates ERalpha and aromatase expression and hypersensitized MCF-7Ca cells to E(2). We show that trastuzumab is beneficial in hormone-refractory cells and xenografts by restoring ER, implicating Her-2 as a negative regulator of ERalpha. In xenograft studies , the combination of trastuzumab plus letrozole is equally effective in inhibiting growth of MCF-7Ca tumors as letrozole alone . However, on the acquisition of resistance and increased Her-2 expression, the combination of letrozole plus trastuzumab provided superior benefit over letrozole or trastuzumab alone.

sentence: In xenograft studies , the combination of trastuzumab plus letrozole is equally effective in inhibiting growth of MCF-7Ca tumors as letrozole alone .
[["trastuzumab", "letrozole", "POS"]]